---
title: "Who cites Hunter Lightman — page 6 — 2,420 citing papers"
description: "2,420 papers of the Elamur Research library cite the works of Hunter Lightman, found in their bibliographies · page 6 of 8 · 501–600; the most…"
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---
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# Who cites Hunter Lightman

2,758 citations of their works from 2,420 papers of our library (of the 149,439 whose bibliographies we read) · 745 with a page here, the most cited first · page 6 of 8 · 501–600 · [← Hunter Lightman](https://md.research.elamur.ai/free/en/authors/hunter-lightman/)

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501. **[Nearest-Neighbor Retrieval for Indigenous Image Captioning](https://md.research.elamur.ai/free/en/papers/vasselli-2026-nearest-neighbor-retrieval-indigenous-image/) [Workshop on NLP for Indigenous Languages of the Americas (AmericasNLP)](https://md.research.elamur.ai/free/en/venues/americasnlp/)**Justin Vasselli, Arturo Martínez Peguero, Shintaro Ozaki, et al.*2026 · 1 citation*
502. **[NEAT: Neuron-Based Early Exit for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-neat-neuron-based-early-exit/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kang Liu, YongKang Liu, Xiaocui Yang, et al.*2026 · 1 citation*
503. **[Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-not-all-tokens-matter-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanbing Liu, Lang Cao, Yuanyi Ren, et al.*2026 · 1 citation*
504. **[OCR or Not? Rethinking Document Information Extraction in the MLLMs Era with Real-World Large-Scale Datasets](https://md.research.elamur.ai/free/en/papers/shen-2026-ocr-or-not-rethinking-document/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Jiyuan Shen, Yuan Peiyue, Atin Ghosh, et al.*2026 · 1 citation*
505. **[On the Step Length Confounding in LLM Reasoning Data Selection](https://md.research.elamur.ai/free/en/papers/wang-2026-step-length-confounding-llm-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bing Wang, Rui Miao, Chen Shen, et al.*2026 · 1 citation*
506. **[Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards](https://md.research.elamur.ai/free/en/papers/pisano-2026-process-reward-models-meet-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Raffaele Pisano, Roberto Navigli*2026 · 1 citation*
507. **[RAFFLES: Reasoning-based Attribution of Faults for LLM Systems](https://md.research.elamur.ai/free/en/papers/zhu-2026-raffles-reasoning-based-attribution-faults/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Chenyang Zhu, Spencer Hong, Jingyu Wu, et al.*2026 · 1 citation*
508. **[Reasoning Fails Where Step Flow Breaks](https://md.research.elamur.ai/free/en/papers/xu-2026-reasoning-fails-where-step-flow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyu Xu, Yulan Pan, Xiaosong Yuan, et al.*2026 · 1 citation*
509. **[Reasoning or Knowledge: Stratified Evaluation of Biomedical LLMs](https://md.research.elamur.ai/free/en/papers/thapa-2026-reasoning-or-knowledge-stratified-evaluation/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Rahul Thapa, Qingyang Wu, Kevin Wu, et al.*2026 · 1 citation*
510. **[Reasoning Up the Instruction Ladder for Controllable Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-reasoning-up-instruction-ladder-controllable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zishuo Zheng, Vidhisha Balachandran, Chan Young Park, et al.*2026 · 1 citation*
511. **[Rectified Sparse Attention for Efficient Long-Sequence Generation](https://md.research.elamur.ai/free/en/papers/sun-2026-rectified-sparse-attention-efficient-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yutao Sun, Tianzhu Ye, Li Dong, et al.*2026 · 1 citation*
512. **[ReProbe: Efficient Test-Time Scaling of Multi-Step Reasoning by Probing Internal States of Large Language Models](https://md.research.elamur.ai/free/en/papers/ni-2026-reprobe-efficient-test-time-scaling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingwei Ni, Ekaterina Fadeeva, Tianyi Wu, et al.*2026 · 1 citation*
513. **[ReTraceQA: Evaluating Reasoning Traces of Small Language Models in Commonsense Question Answering](https://md.research.elamur.ai/free/en/papers/molfese-2026-retraceqa-evaluating-reasoning-traces-small/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Francesco Maria Molfese, Luca Moroni, Ciro Porcaro, et al.*2026 · 1 citation*
514. **[Scaling Test-Time Compute to Achieve IOI Gold Medal with Open-Weight Models](https://md.research.elamur.ai/free/en/papers/samadi-2026-scaling-test-time-compute-achieve/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mehrzad Samadi, Aleksander Ficek, Sean Narenthiran, et al.*2026 · 1 citation*
515. **[Sense and Sensitivity: “Reasoning” Models are More Robust, but can Diverge from Human Consensus in a Legal Interpretation Task](https://md.research.elamur.ai/free/en/papers/petersen-2026-sense-sensitivity-reasoning-models-are/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Dawson Petersen, Abhishek Purushothama, Nathan Schneider*2026 · 1 citation*
516. **[Solve-Detect-Verify: Inference-Time Scaling with Flexible Generative Verifier](https://md.research.elamur.ai/free/en/papers/zhong-2026-solve-detect-verify-inference-time/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianyuan Zhong, Zeju Li, Zhijian Xu, et al.*2026 · 1 citation*
517. **[Synthetic Function Demonstrations Improve Generation in Low-Resource Programming Languages](https://md.research.elamur.ai/free/en/papers/mckenna-2026-synthetic-function-demonstrations-improve-generation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Nick McKenna, Xinnuo Xu, Jack Williams, et al.*2026 · 1 citation*
518. **[Takoyaki at SemEval-2026 Task 3: Ensembling LLM Predictions using Demonstration Retrieval for Dimensional Aspect-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/yamada-2026-takoyaki-semeval-2026-task-3/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Kosuke Yamada, Sho Takase, Ryosuke Kohita*2026 · 1 citation*
519. **[Team QUESPA System Submission for the IWSLT 2026 Dialectal and Low-resource Speech Translation Task](https://md.research.elamur.ai/free/en/papers/ortega-2026-team-quespa-system-submission-iwslt/) [International Conference on Spoken Language Translation (IWSLT)](https://md.research.elamur.ai/free/en/venues/iwslt/)**John E. Ortega, Rodolfo Joel Zevallos, Fabrício Carraro, et al.*2026 · 1 citation*
520. **[The Bidirectional Process Reward Model](https://md.research.elamur.ai/free/en/papers/zhang-2026-bidirectional-process-reward-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingyin Zhang, Jun Gao, Xiaoxue Ren, et al.*2026 · 1 citation*
521. **[Thinking Long, but Short: Stable Sequential Test-Time Scaling for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/metel-2026-thinking-long-but-short-stable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Michael R. Metel, Yufei Cui, Boxing Chen, et al.*2026 · 1 citation*
522. **[Thinking with Reasoning Skills: Fewer Tokens, More Accuracy](https://md.research.elamur.ai/free/en/papers/zhao-2026-thinking-reasoning-skills-fewer-tokens/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guangxiang Zhao, Qilong Shi, Xusen Xiao, et al.*2026 · 1 citation*
523. **[Training Language Models to Use Prolog as a Tool](https://md.research.elamur.ai/free/en/papers/mellgren-2026-training-language-models-use-prolog/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Niklas Mellgren, Peter Schneider-Kamp, Lukas Galke Poech*2026 · 1 citation*
524. **[When Is Thinking Enough? Early Exit via Sufficiency Assessment for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/xiang-2026-when-is-thinking-enough-early/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Xiang, Yixin Ji, Ruotao Xu, et al.*2026 · 1 citation*
525. **[When Models Outthink Their Safety: Unveiling and Mitigating Self-Jailbreak in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/mao-2026-when-models-outthink-their-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingzhi Mao, Chunkang Zhang, Junxiang Wang, et al.*2026 · 1 citation*
526. **[Where Reasoning Breaks: Logic-Aware Path Selection by Controlling Logical Connectives in LLMs Reasoning Chains](https://md.research.elamur.ai/free/en/papers/park-2026-where-reasoning-breaks-logic-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Seunghyun Park, Yuanyuan Lei*2026 · 1 citation*
527. **[x1: Learning to Think Adaptively Across Languages and Cultures](https://md.research.elamur.ai/free/en/papers/ye-2026-x1-learning-think-adaptively-across/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangfan Ye, Xiaocheng Feng, Xiachong Feng, et al.*2026 · 1 citation*
528. **[AraEval: An Arabic Multi-Task Evaluation Suite for Large Language Models](https://md.research.elamur.ai/free/en/papers/althnian-2025-araeval-arabic-multi-task-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Alhanoof Althnian, Norah A. Alzahrani, Shaykhah Z. Alsubaie, et al.*2025 · 1 citation*
529. **[A Comprehensive Survey of Process Reward Models: Data Generation, Model Construction, and Usage](https://md.research.elamur.ai/free/en/papers/zheng-2026-comprehensive-survey-process-reward-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Congmin Zheng, Jiachen Zhu, Zhuoying Ou, et al.*2026*
530. **[A Simple and Efficient Learning-Style Prompting for LLM Jailbreaking](https://md.research.elamur.ai/free/en/papers/luo-2026-simple-efficient-learning-style-prompting/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuan Luo, Yue Wang, Zefeng He, et al.*2026*
531. **[A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions](https://md.research.elamur.ai/free/en/papers/yu-2026-survey-reinforcement-learning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.*2026*
532. **[AAPO: Enhancing the Reasoning Capabilities of LLMs with Advantage Margin](https://md.research.elamur.ai/free/en/papers/xiong-2026-aapo-enhancing-reasoning-capabilities-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jian Xiong, Jingbo Zhou, Jingyong Ye, et al.*2026*
533. **[Action Boundary Blindness: When LLM Agents Cannot Tell Where One Action Ends and Another Begins](https://md.research.elamur.ai/free/en/papers/wang-2026-action-boundary-blindness-when-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhangyi Wang, Bingnan Yu, Jiexiang Xu, et al.*2026*
534. **[AdaJudge: Adaptive Multi-Perspective Judging for Reward Modeling](https://md.research.elamur.ai/free/en/papers/miao-2026-adajudge-adaptive-multi-perspective-judging/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongliang Miao, Yangyang Liang, Mengnan Du*2026*
535. **[AdaMix: Adaptive Mixing for Short and Long Reasoning Adapters](https://md.research.elamur.ai/free/en/papers/luo-2026-adamix-adaptive-mixing-short-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Luo, Xiao Yan, Xinyan Li, et al.*2026*
536. **[Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations](https://md.research.elamur.ai/free/en/papers/zuo-2026-adaptive-test-time-compute-allocation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bowen Zuo, Dongruo Zhou, Yinglun Zhu*2026*
537. **[Advancing Reasoning in Diffusion Language Models with Denoising Process Rewards](https://md.research.elamur.ai/free/en/papers/xie-2026-advancing-reasoning-diffusion-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaoan Xie, Lingjing Kong, Xiangchen Song, et al.*2026*
538. **[AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages](https://md.research.elamur.ai/free/en/papers/yu-2026-afriquellm-how-data-mixing-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Yu, Tianyi Xu, Michael A. Hedderich, et al.*2026*
539. **[Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents](https://md.research.elamur.ai/free/en/papers/yehudai-2026-agentic-clear-automating-multi-level/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Asaf Yehudai, Lilach Eden, Michal Shmueli-Scheuer*2026*
540. **[AgenticQwen: Training Small Agentic Language Models with Dual Data Flywheels for Industrial-Scale Tool Use](https://md.research.elamur.ai/free/en/papers/lyu-2026-agenticqwen-training-small-agentic-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanjie Lyu, Chengyu Wang, Haonan Zheng, et al.*2026*
541. **[AgentV-RL: Scaling Reward Modeling with Agentic Verifier](https://md.research.elamur.ai/free/en/papers/zhang-2026-agentv-rl-scaling-reward-modeling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiazheng Zhang, Ziche Fu, Zhiheng Xi, et al.*2026*
542. **[Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling](https://md.research.elamur.ai/free/en/papers/wang-2026-aligning-agents-planning-benchmark-trajectory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaxuan Wang, Yulan Hu, Wenjin Yang, et al.*2026*
543. [**AppTek Call-Center Dialogues: A Multi-Accent Long-Form Benchmark for English ASR arXiv:2604.27543**Eugen Beck, Sarah Beranek, Uma Moothiringote, et al.*2026*](https://md.research.elamur.ai/free/en/papers/beck-2026-apptek-call-center-dialogues-multi/)
544. [**Arabic Morphosyntactic Tagging and Dependency Parsing with Large Language Models**Mohamed Adel, Bashar Alhafni, Nizar Habash*2026*](https://md.research.elamur.ai/free/en/papers/adel-2026-arabic-morphosyntactic-tagging-dependency-parsing/)
545. [**ArabiGEE: A Hierarchical Taxonomy for Arabic Grammatical Error Explanation arXiv:2606.10765**Khaled Elhady, Omar Kallas, Nizar Habash, et al.*2026*](https://md.research.elamur.ai/free/en/papers/elhady-2026-arabigee-hierarchical-taxonomy-arabic-grammatical/)
546. [**AraGenre 2026: A Hierarchical Definition-Guided Arabic Genre Classification Shared Task arXiv:2609.27387 · The 4th ArabicNLP conference at EMNLP 2026**Mo El-Haj, Saad Ezzini, Shadi Abudalfa, et al.*2026*](https://md.research.elamur.ai/free/en/papers/el-haj-2026-aragenre-2026-hierarchical-definition-guided/)
547. **[Arguments that Alter Minds: LLM Rationales Sway Human (and LLM) Notions of Plausibility](https://md.research.elamur.ai/free/en/papers/palta-2026-arguments-that-alter-minds-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shramay Palta, Peter A. Rankel, Sarah Wiegreffe, et al.*2026*
548. **[ARM2: Adaptive Reasoning Model with Vision Understanding and Executable Code](https://md.research.elamur.ai/free/en/papers/xie-2026-arm2-adaptive-reasoning-model-vision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jian Xie, Zhendong Chu, Aoxiao Zhong, et al.*2026*
549. **[ArrowGEV: Grounding Events in Video via Learning the Arrow of Time](https://md.research.elamur.ai/free/en/papers/yu-2026-arrowgev-grounding-events-video-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fangxu Yu, Ziyao Lu, Liqiang Niu, et al.*2026*
550. **[As Easy as Rocket Science: Assessing the Ability of Large Language Models to Interpret Negation in Figurative Language](https://md.research.elamur.ai/free/en/papers/owers-2026-as-easy-as-rocket-science/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jasmine Owers, Edwin Simpson, Martha Lewis*2026*
551. **[Ascending the Infinite Ladder: Benchmarking Spatial Deformation Reasoning in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-ascending-infinite-ladder-benchmarking-spatial/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiahuan Zhang, Shunwen Bai, Tianheng Wang, et al.*2026*
552. [**Auditing Discovery Claims: A Two-Sided Criterion for Agentic Science, with the Negative Side Decidable arXiv:2608.00981**Wenhui Chen, Jianlin Chen, Ziyao Lin, et al.*2026*](https://md.research.elamur.ai/free/en/papers/chen-2026-auditing-discovery-claims-two/)
553. **[AutoSearch: Adaptive Search Depth for Efficient Agentic RAG via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/sun-2026-autosearch-adaptive-search-depth-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingbo Sun, Wenyue Chong, Songjun Tu, et al.*2026*
554. **[Benchmarking Post-Training Quantization of Large Language Models under Microscaling Floating Point Formats](https://md.research.elamur.ai/free/en/papers/zhang-2026-benchmarking-post-training-quantization-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Manyi Zhang, Ji-Fu Li, Zhongao Sun, et al.*2026*
555. **[Beyond Accuracy: Alignment and Error Detection across Languages in the Bi-GSM8K Math-Teaching Benchmark](https://md.research.elamur.ai/free/en/papers/park-2026-beyond-accuracy-alignment-error-detection/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jieun Park, KyungTae Lim, Joon-ho Lim*2026*
556. **[Beyond Examples: Towards Automated Thought-level In-Context Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-examples-automated-thought-level/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinyang Wu, Mingkuan Feng, Shuai Zhang, et al.*2026*
557. **[Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-length-scaling-synergizing-breadth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiyuan Zhang, Yufei Wang, Tianhe Wu, et al.*2026*
558. **[Beyond Query Memorization: Large Language Model Routing with Query Decomposition and Historical Matching](https://md.research.elamur.ai/free/en/papers/lv-2026-beyond-query-memorization-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bo Lv, Jingbo Sun, Jianwei Lv, et al.*2026*
559. **[Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/phan-2026-beyond-reasoning-gains-mitigating-general/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hoang Phan, Xianjun Yang, Yuanshun Yao, et al.*2026*
560. **[Beyond Sample-Level Feedback: Using Reference-Level Feedback to Guide Data Synthesis](https://md.research.elamur.ai/free/en/papers/mehri-2026-beyond-sample-level-feedback-reference/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Shuhaib Mehri, Xiusi Chen, Heng Ji, et al.*2026*
561. **[Beyond Simple Term Injection: Reasoning Models for Legal Translation in a Non-Dominant Language Variety](https://md.research.elamur.ai/free/en/papers/natale-2026-beyond-simple-term-injection-reasoning/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Paolo Di Natale, Elena Chiocchetti, Marlies Alber, et al.*2026*
562. **[Boosting Self-Consistency with Ranking](https://md.research.elamur.ai/free/en/papers/marina-2026-boosting-self-consistency-ranking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Maria Marina, Daniil Moskovskiy, Sergey Pletenev, et al.*2026*
563. **[Building a Custom Taxonomy of AI Skills and Tasks from the Ground Up with Job Postings](https://md.research.elamur.ai/free/en/papers/meisenbacher-2026-building-custom-taxonomy-ai-skills/) [Workshop on Customizable NLP: Progress and Challenges in Customizing NLP for a Domain, Application, Group, or Individual](https://md.research.elamur.ai/free/en/venues/customnlp4u/)**Stephen Meisenbacher, Peter Norlander*2026*
564. **[Calibration-Aware Policy Optimization for Reasoning LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-calibration-aware-policy-optimization-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqi Wang, Xingzhou Lou, Meiqi Wu, et al.*2026*
565. **[Can LLMs Really Judge? A Progressive Argumentation-Mining Framework for Distinguishing Understanding from Aggregation](https://md.research.elamur.ai/free/en/papers/wang-2026-can-llms-really-judge-progressive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fuyu Wang, Jiangtong Li, Kun Zhu, et al.*2026*
566. **[CEMT:Controllable Element-Oriented Machine Translation via Structured Linguistic Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2026-cemt-controllable-element-oriented-machine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lingling Shi, Haoyu Jin, Ruiyu Fang, et al.*2026*
567. **[ChartDiff: A Large-Scale Benchmark for Comprehending Pairs of Charts](https://md.research.elamur.ai/free/en/papers/ye-2026-chartdiff-large-scale-benchmark-comprehending/) [Workshop on Advances in Language and Vision Research (ALVR)](https://md.research.elamur.ai/free/en/venues/alvr/)**Rongtian Ye*2026*
568. **[ChildEval:WHEN LARGE LANGUAGE MODELS MEET CHILDREN'S PERSONALITIES](https://md.research.elamur.ai/free/en/papers/luo-2026-childeval-when-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanyan Luo, Xue Han, Chunxu Zhao, et al.*2026*
569. **[Chinese Court Simulation with LLM-Based Agents System](https://md.research.elamur.ai/free/en/papers/zhang-2026-chinese-court-simulation-llm-based/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaiyuan Zhang, Jiaqi Li, Yueyue Wu, et al.*2026*
570. **[Choose Your Lens: Multi-Perspective Value Alignment of Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/zhao-2026-choose-your-lens-multi-perspective/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gejian Zhao, Hanzhou Wu, Xinpeng Zhang*2026*
571. **[Chronos: Learning Temporal Dynamics of Reasoning Chains for Test-Time Scaling](https://md.research.elamur.ai/free/en/papers/zhang-2026-chronos-learning-temporal-dynamics-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Zhang, Jiayi Liao, Chengpeng Li, et al.*2026*
572. **[CLaC at SemEval-2026 Task 6: Response Clarity Detection in Political Discourse](https://md.research.elamur.ai/free/en/papers/turk-2026-clac-semeval-2026-task-6/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Nawar Turk, Lucas Miquet-Westphal, Leila Kosseim*2026*
573. **[CLARO: Controlled Attribute-Driven Reasoning Optimization for Efficient Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/schlesinger-2026-claro-controlled-attribute-driven-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Oded Schlesinger, Young Kyung Kim, J. Matias Di Martino, et al.*2026*
574. **[CodeRise: Bootstrapping LLMs for Ultra Low-Resource Programming Languages via Progressive Self-Refinement Curriculum](https://md.research.elamur.ai/free/en/papers/wen-2026-coderise-bootstrapping-llms-ultra-low/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengfei Wen, Xuanang Chen, Ben He, et al.*2026*
575. **[CodeRM-NT: Reward Model for Code RL without Unit Tests](https://md.research.elamur.ai/free/en/papers/xia-2026-coderm-nt-reward-model-code/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiao Xia, Dan Zhang, Tianrui Sun*2026*
576. **[CogGen: A Cognitively Inspired Recursive Framework for Deep Research Report Generation](https://md.research.elamur.ai/free/en/papers/tian-2026-coggen-cognitively-inspired-recursive-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kuo Tian, Pengfei Sun, Zhen Wu, et al.*2026*
577. **[Cognitive Analysis Graph-Guided Multi-Turn Safety Enhancement for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-cognitive-analysis-graph-guided-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lanxue Zhang, Yuqiang Xie, Fang Fang, et al.*2026*
578. **[Confidence-Weighted Token Set Cover for Early Hypothesis Pruning in Self-Consistency](https://md.research.elamur.ai/free/en/papers/sultan-2026-confidence-weighted-token-set-cover/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Arafat Sultan, Ramón Fernandez Astudillo*2026*
579. **[ConMA : Confidence-Guided Kernel Sampling with Multi-Stage Aggregation for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-conma-confidence-guided-kernel-sampling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yinuo Wang, Qingjie Li, Wenyao Cui, et al.*2026*
580. **[CoTEvol: Self-Evolving Chain-of-Thoughts for Data Synthesis in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-cotevol-self-evolving-chain-thoughts/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuo Wang, Zhuo Zhang, Yafu Li, et al.*2026*
581. **[Crossing the Reward Bridge: Expanding Reinforcement Learning with Verifiable Rewards Across Diverse Domains](https://md.research.elamur.ai/free/en/papers/su-2026-crossing-reward-bridge-expanding-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Su, Dian Yu, Linfeng Song, et al.*2026*
582. **[Curing Miracle Steps in LLM Mathematical Reasoning with Rubric Rewards](https://md.research.elamur.ai/free/en/papers/yuan-2026-curing-miracle-steps-llm-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youliang Yuan, Qiuyang Mang, Jingbang Chen, et al.*2026*
583. **[CxMP: A Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models](https://md.research.elamur.ai/free/en/papers/oba-2026-cxmp-linguistic-minimal-pair-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Miyu Oba, Saku Sugawara*2026*
584. **[C³D: Enhancing LLM Reasoning via Confidence-Guided Contrastive Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-c-3-d-enhancing-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yufeng Zhang, Xuepeng Wang, Lingxiang Wu, et al.*2026*
585. **[Detecting Latin in Historical Books with Large Language Models: A Multimodal Benchmark](https://md.research.elamur.ai/free/en/papers/wu-2026-detecting-latin-historical-books-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yu Wu, Ke Shu, Jonas Fischer, et al.*2026*
586. **[DialDefer: A Framework for Detecting and Mitigating LLM Dialogic Deference](https://md.research.elamur.ai/free/en/papers/rabbani-2026-dialdefer-framework-detecting-mitigating-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Parisa Rabbani, Priyam Sahoo, Ruben Mathew, et al.*2026*
587. **[Do Emotions Influence Moral Judgment in Large Language Models?](https://md.research.elamur.ai/free/en/papers/saim-2026-do-emotions-influence-moral-judgment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mohammad Saim, Tianyu Jiang*2026*
588. **[Does Chain-of-Thought Reasoning Help Mobile GUI Agents? An Empirical Study](https://md.research.elamur.ai/free/en/papers/zhang-2026-does-chain-thought-reasoning-help/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Li Zhang, Longxi Gao, Mengwei Xu*2026*
589. **[Does RLVR Extend Reasoning Boundaries? Investigating Capability Expansion in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/shen-2026-does-rlvr-extend-reasoning-boundaries/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minghe Shen, Zhuo Zhi, Chonghan Liu, et al.*2026*
590. **[Don't Tell the Answer, Truly Guide the Reasoning During RL Rollouts](https://md.research.elamur.ai/free/en/papers/wang-2026-don-t-tell-answer-truly/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyi Wang, Jinyi Han, Zishang Jiang, et al.*2026*
591. **[DORA: A Dual-Objective Reinforcement Learning Framework for Effective and Efficient Multimodal Agentic Search](https://md.research.elamur.ai/free/en/papers/qin-2026-dora-dual-objective-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guangming Qin, Yuhao Deng, Yukun Zhao, et al.*2026*
592. **[DOS: Dependency-Oriented Sampler for Masked Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-dos-dependency-oriented-sampler-masked/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xueyu Zhou, Yangrong Hu, Jian Huang*2026*
593. **[E-ViC: Reasoning Beyond Text via Embodied Visual Chain for Spatial Intelligence](https://md.research.elamur.ai/free/en/papers/qi-2026-e-vic-reasoning-beyond-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junbo Qi, Yi Zhang, Hanchu Ni, et al.*2026*
594. **[EduMARS: Can Vision-Language Models Grade Like Teachers? Benchmarking Multimodal, Rubric-Based Assessment on Chinese K-12 Answers](https://md.research.elamur.ai/free/en/papers/zhao-2026-edumars-can-vision-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuan Zhao, Jiashun Chen, Wanting xu, et al.*2026*
595. **[Efficient KL Divergence Estimation via Truncated Top-K Integration for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-efficient-kl-divergence-estimation-truncated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyuan Wang, Luozhijie Jin, Bo Wang, et al.*2026*
596. **[Enhancing LLM-based Search Agents via Contribution Weighted Group Relative Policy Optimization](https://md.research.elamur.ai/free/en/papers/wang-2026-enhancing-llm-based-search-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junzhe Wang, Zhiheng Xi, Yajie Yang, et al.*2026*
597. **[EntroBench: Evaluating LLM Watermarking Under Multi-Entropy Scenarios and Practical User Operations](https://md.research.elamur.ai/free/en/papers/qin-2026-entrobench-evaluating-llm-watermarking-under/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pengyuan Qin, Linnan Tu, Yuhan Ke, et al.*2026*
598. **[Entropy Scheduling in Reinforcement Learning for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-entropy-scheduling-reinforcement-learning-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingjin Wang, Howe Tissue, Lu Wang, et al.*2026*
599. **[Escaping the Sisyphus Dilemma: Experience Replay for Robust Text-to-Optimization Modeling](https://md.research.elamur.ai/free/en/papers/xie-2026-escaping-sisyphus-dilemma-experience-replay/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wantong Xie, Yinghao Chen, Yi-Xiang Hu, et al.*2026*
600. **[ETR: Entropy Trend Reward for Efficient Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/xiong-2026-etr-entropy-trend-reward-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuan Xiong, Huan Liu, Li Gu, et al.*2026*

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