---
title: "Who cites Eric Tang — page 8 — 2,152 papers of our library"
description: "2,152 papers of the Elamur Research library cite the works of Eric Tang, found in their bibliographies · page 8 of 9 · 701–800; the most cited first."
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---
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# Who cites Eric Tang

2,176 citations of their works from 2,152 papers of our library (of the 149,439 whose bibliographies we read) · 844 with a page here, the most cited first · page 8 of 9 · 701–800 · [← Eric Tang](https://md.research.elamur.ai/free/en/authors/eric-tang/)

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701. **[RACER: Retrieval-Augmented Contextual Rapid Speculative Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-racer-retrieval-augmented-contextual-rapid/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihong Zhang, Zuchao Li, Lefei Zhang, et al.*2026 · 1 citation*
702. **[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*
703. **[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*
704. **[ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments](https://md.research.elamur.ai/free/en/papers/wang-2026-reasoningguard-safeguarding-large-reasoning-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuquan Wang, Mi Zhang, Yining Wang, et al.*2026 · 1 citation*
705. **[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*
706. **[Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-render-thought-rendering-textual-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifan Wang, Shiyu Li, Peiming Li, et al.*2026 · 1 citation*
707. **[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*
708. **[RISER: Orchestrating Latent Reasoning Skills for Adaptive Activation Steering](https://md.research.elamur.ai/free/en/papers/ye-2026-riser-orchestrating-latent-reasoning-skills/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wencheng Ye, Xiaoyang Yuan, Yi Bin, et al.*2026 · 1 citation*
709. **[Seeing but Not Thinking: Routing Distraction in Multimodal Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/xu-2026-seeing-but-not-thinking-routing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haolei Xu, Haiwen Hong, Hongxing Li, et al.*2026 · 1 citation*
710. **[SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs](https://md.research.elamur.ai/free/en/papers/sun-2026-sepseq-training-free-framework-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Sun, Yu Liu, Lu Han, et al.*2026 · 1 citation*
711. **[SmartAD: Capacity-Aligned Agent Distillation for Small Language Models](https://md.research.elamur.ai/free/en/papers/tang-2026-smartad-capacity-aligned-agent-distillation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guokai Tang, Feng Zhao*2026 · 1 citation*
712. **[TELL-TALE: Task Efficient LLMs with Task Aware Layer Elimination](https://md.research.elamur.ai/free/en/papers/naim-2026-tell-tale-task-efficient-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Omar Naim, Krish Sharma, Niyar R Barman, et al.*2026 · 1 citation*
713. **[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*
714. **[Think in Sentences: Explicit Sentence Boundaries Enhance Language Model's Capabilities](https://md.research.elamur.ai/free/en/papers/liu-2026-think-sentences-explicit-sentence-boundaries/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhichen Liu, Yongyuan Li, Yang Xu*2026 · 1 citation*
715. **[ThinkBrake: Efficient Reasoning via Log-Probability Margin Guided Decoding](https://md.research.elamur.ai/free/en/papers/song-2026-thinkbrake-efficient-reasoning-log-probability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sangjun Song, Minjae Oh, Seungkyu Lee, et al.*2026 · 1 citation*
716. **[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*
717. **[Towards Stable and Effective Reinforcement Learning for Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/zhang-2026-stable-effective-reinforcement-learning-mixture/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Di Zhang, Xun Wu, Shaohan Huang, et al.*2026 · 1 citation*
718. **[When Do Large Language Models Exhibit Unsolicited Deception?](https://md.research.elamur.ai/free/en/papers/taylor-2026-when-do-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Samuel M. Taylor, Benjamin K. Bergen*2026 · 1 citation*
719. **[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*
720. [**GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs? arXiv:2412.10056**Zhikai Lei, Tianyi Liang, Hanglei Hu, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/lei-2024-gaokao-eval-high-scores/)
721. **[A Scalable Multi-LLM Collaboration System with Retrieval-based Selection and Exploration-Exploitation-Driven Enhancement](https://md.research.elamur.ai/free/en/papers/tang-2026-scalable-multi-llm-collaboration-system/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shengji Tang, Jianjian Cao, Weihao Lin, et al.*2026*
722. **[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*
723. **[Accelerating LLM Fine-Tuning via Embedding Knowledge Transfer](https://md.research.elamur.ai/free/en/papers/peng-2026-accelerating-llm-fine-tuning-embedding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Meishu Peng, Ziyue Zhang, Yi Zhang, et al.*2026*
724. **[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*
725. **[Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-agent-gwo-collaborative-agents-dynamic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xudong Wang, Chaoning Zhang, Chenghao Li, et al.*2026*
726. **[AgentGL: Towards Agentic Graph Learning with LLMs via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/sun-2026-agentgl-agentic-graph-learning-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanfu Sun, Kang Li, Dongzhe Fan, et al.*2026*
727. **[AlgBench: To What Extent Do Large Reasoning Models Understand Algorithms?](https://md.research.elamur.ai/free/en/papers/sun-2026-algbench-what-extent-do-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Henan Sun, Kaichi Yu, Yuyao Wang, et al.*2026*
728. **[Attribution-Based Analysis and Optimization of Modular Agentic Workflows](https://md.research.elamur.ai/free/en/papers/yang-2026-attribution-based-analysis-optimization-modular/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingxuan Yang, Bo Huang, Siyuan Qi, et al.*2026*
729. **[BayesFlow: A Probability Inference Framework for Meta-Agent Assisted Workflow Generation](https://md.research.elamur.ai/free/en/papers/yuan-2026-bayesflow-probability-inference-framework-meta/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bo Yuan, Yun Zhou, Zhichao Xu, et al.*2026*
730. **[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*
731. **[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*
732. **[Beyond the Singular: Revealing the Value of Multiple Generations in Benchmark Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-singular-revealing-value-multiple/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenbo Zhang, Hengrui Cai, Wenyu Chen*2026*
733. **[Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language Models](https://md.research.elamur.ai/free/en/papers/zou-2026-breaking-block-boundaries-anchor-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shun Zou, Yong Wang, Zehui Chen, et al.*2026*
734. **[Breaking the Impasse: Dual-Scale Evolutionary Policy Training for Social Language Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-breaking-impasse-dual-scale-evolutionary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minzheng Wang, Run Luo, Yanbo Wang, et al.*2026*
735. **[Calibrated Progressive Distillation: Co-Designing Curriculum and Target Mixing for Knowledge Distillation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-calibrated-progressive-distillation-co-designing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mengxiang Zhang, Lingyuan Liu*2026*
736. **[Calibrated Speculative Decoding: Frequency-Guided Candidate Selection for Efficient Inference](https://md.research.elamur.ai/free/en/papers/zhouxuwen-2026-calibrated-speculative-decoding-frequency-guided/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhouxuwen, Fangxin Liu, Chao Wang, et al.*2026*
737. **[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*
738. **[Concise Math Reasoning via Difficulty-Aware Distillation](https://md.research.elamur.ai/free/en/papers/wu-2026-concise-math-reasoning-difficulty-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifan Wu, Jingze Shi, Bingheng Wu, et al.*2026*
739. **[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*
740. **[Consistency of LLMs to Comparative Statements in Mathematical Reasoning Tasks](https://md.research.elamur.ai/free/en/papers/san-2026-consistency-llms-comparative-statements-mathematical/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aidan W. San, Daniel Juyoung Son, Xiaodong Liu, et al.*2026*
741. **[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*
742. **[CreditDecoding: Accelerating Parallel Decoding in Diffusion Large Language Models with Trace Credit](https://md.research.elamur.ai/free/en/papers/wang-2026-creditdecoding-accelerating-parallel-decoding-diffusion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kangyu Wang, Zhiyun Jiang, Haibo Feng, et al.*2026*
743. **[Critical-CoT: A Robust Defense Framework against Reasoning-Level Backdoor Attacks in Large Language Models](https://md.research.elamur.ai/free/en/papers/truong-2026-critical-cot-robust-defense-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vu Tuan Truong, Long Bao Le*2026*
744. **[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*
745. **[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*
746. **[Data Efficient RLVR via Off-Policy Influence Guidance](https://md.research.elamur.ai/free/en/papers/zhu-2026-data-efficient-rlvr-off-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Erle Zhu, Dazhi Jiang, Yuan Wang, et al.*2026*
747. **[DecoCal: Decoding with Calibration in Diffusion Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-decocal-decoding-calibration-diffusion-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fan Xu, Huixuan Zhang, Xiaojun Wan*2026*
748. **[Decoupling Generalization and Adaptation in Meta-Learning for Large Language Models](https://md.research.elamur.ai/free/en/papers/vetcha-2026-decoupling-generalization-adaptation-meta-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nitin Vetcha, Binqian Xu, Dianbo Liu*2026*
749. **[Detecting Hallucinations in Authentic LLM–Human Interactions](https://md.research.elamur.ai/free/en/papers/ren-2026-detecting-hallucinations-authentic-llm-human/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yujie Ren, Niklas Gruhlke, Anne Lauscher*2026*
750. **[Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decoding](https://md.research.elamur.ai/free/en/papers/yun-2026-distilling-long-cot-reasoning-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taewon Yun, Jisu Shin, Jeonghwan Choi, et al.*2026*
751. **[Distributional Clarity: The Hidden Driver of RL-Friendliness in Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-distributional-clarity-hidden-driver-rl/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaoning Sun, Mingzhu Cai, Huang He, et al.*2026*
752. **[Do We Always Need Query-Level Workflows? Rethinking Agentic Workflow Generation for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/wang-2026-do-we-always-need-query/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zixu Wang, Bingbing Xu, Yige Yuan, et al.*2026*
753. **[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*
754. **[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*
755. **[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*
756. **[EpiCaR: Knowing What You Don't Know Matters for Better Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/yeom-2026-epicar-knowing-what-you-don/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jewon Yeom, Jaewon Sok, Seonghyeon Park, et al.*2026*
757. **[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*
758. **[Exploiting Tree Structure for Credit Assignment in Reinforcement Learning with Large Language Models](https://md.research.elamur.ai/free/en/papers/tran-2026-exploiting-tree-structure-credit-assignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hieu Tran, Zonghai Yao, Hong yu*2026*
759. **[Exploring Layer Activation Dynamic of CoT via Knowledge Probe](https://md.research.elamur.ai/free/en/papers/zhang-2026-exploring-layer-activation-dynamic-cot/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chuanxin Zhang, Jiajun Liu, Yao He, et al.*2026*
760. **[FLAIR: Steering LLM Mathematical Problem Solving based on A Fuzzy-Logic-AssIsted Reasoner](https://md.research.elamur.ai/free/en/papers/wu-2026-flair-steering-llm-mathematical-problem/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Wu, Hongru Sun, Wanqing Li, et al.*2026*
761. **[Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model Factuality](https://md.research.elamur.ai/free/en/papers/zhang-2026-follow-path-reasoning-over-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mike Zhang, Johannes Bjerva, Russa Biswas*2026*
762. **[From Benchmarks to Skills: Low-Rank Factors for LLM Evaluation](https://md.research.elamur.ai/free/en/papers/maimon-2026-benchmarks-skills-low-rank-factors/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Aviya Maimon, Amir David Nisan Cohen, Gal Vishne, et al.*2026*
763. **[From Tokens to Steps: Verification-Aware Speculative Decoding for Efficient Multi-Step Reasoning](https://md.research.elamur.ai/free/en/papers/purohit-2026-tokens-steps-verification-aware-speculative/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kiran Purohit, Ramasuri Narayanam, Soumyabrata Pal*2026*
764. **[FusionFlow: Enabling Deep Structural Exploration for Automated Agentic Workflow Generation](https://md.research.elamur.ai/free/en/papers/wang-2026-fusionflow-enabling-deep-structural-exploration/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiang Wang, Zongtao Yang, Zhuojian Hong, et al.*2026*
765. **[GALA: Geometric Data Selection with Strategic Prospecting for Large Language Model Self-training](https://md.research.elamur.ai/free/en/papers/xie-2026-gala-geometric-data-selection-strategic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhongwei Xie, Ruihao Liao, Zimo Wang, et al.*2026*
766. **[GATE: Graph-based Adaptive Tool Evolution Across Diverse Tasks](https://md.research.elamur.ai/free/en/papers/luo-2026-gate-graph-based-adaptive-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianwen Luo, Yiming Huang, Jinxiang Meng, et al.*2026*
767. **[Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment](https://md.research.elamur.ai/free/en/papers/zhang-2026-generalizable-llm-learning-graph-synthetic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yizhuo Zhang, Heng Wang, Shangbin Feng, et al.*2026*
768. **[GIFT: Guided Fine-Tuning and Transfer for Enhancing Instruction-Tuned Language Models](https://md.research.elamur.ai/free/en/papers/ruan-2026-gift-guided-fine-tuning-transfer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiwen Ruan, Yichao Du, Jianjie Zheng, et al.*2026*
769. **[Good Reasoning Makes Good Demonstrations: Implicit Reasoning Quality Supervision via In-Context Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mei-2026-good-reasoning-makes-good-demonstrations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tiehua Mei, Minxuan Lv, Leiyu Pan, et al.*2026*
770. **[Grammar Search for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/singh-2026-grammar-search-multi-agent-systems/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mayank Singh, Vikas Yadav, Shiva Krishna Reddy Malay, et al.*2026*
771. **[GraphMind: LLMs as Dynamic Knowledge Builders for Sequential Decision-Making](https://md.research.elamur.ai/free/en/papers/shin-2026-graphmind-llms-as-dynamic-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sunguk Shin, Hayeong Lee, Jun Ho Seo, et al.*2026*
772. **[GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy Inputs](https://md.research.elamur.ai/free/en/papers/zhang-2026-gsm-noise-exploring-enhancing-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengxin Zhang, Chengyu Huang, Xufu Liu, et al.*2026*
773. **[Hebbian-Guided Bi-Directional Rank Adaptation for Parameter-Efficient Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhao-2026-hebbian-guided-bi-directional-rank/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xing Zhao, Liu Yang, Xi-Le Zhao, et al.*2026*
774. **[Hetero-Designer: Automated Design of Multi-Agent Systems with Heterogeneous LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-hetero-designer-automated-design-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiheng Zhang, Yuanzhe Zhang, Bohan Yu, et al.*2026*
775. **[InstructDiff: Domain-Adaptive Data Selection via Contrastive Entropy for Efficient LLM Fine-Tuning](https://md.research.elamur.ai/free/en/papers/su-2026-instructdiff-domain-adaptive-data-selection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyou Su, He Zhu, Xiao Luo, et al.*2026*
776. **[Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains](https://md.research.elamur.ai/free/en/papers/yuan-2026-knowledge-verification-exploring-rlvr-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhonghang Yuan, Zhefan Wang, Fang Hu, et al.*2026*
777. **[Language Models Learn Universal Representations of Numbers and Here's Why You Should Care](https://md.research.elamur.ai/free/en/papers/stefanik-2026-language-models-learn-universal-representations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michal Štefánik, Timothee Mickus, Marek Kadlčík, et al.*2026*
778. **[Large-Scale Diverse Synthesis for Mid-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-large-scale-diverse-synthesis-mid/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuemiao Zhang, Chengying Tu, Can Ren, et al.*2026*
779. **[Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and Refinement](https://md.research.elamur.ai/free/en/papers/sun-2026-learning-cognition-enhancing-rl-efficiency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zexu Sun, Yongcheng Zeng, Erxue Min, et al.*2026*
780. **[Learning from Mistakes: Negative Reasoning Samples Enhance Out-of-Domain Generalization](https://md.research.elamur.ai/free/en/papers/xueyun-2026-learning-mistakes-negative-reasoning-samples/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tian Xueyun, MingHua Ma, Bingbing Xu, et al.*2026*
781. **[Learning to Refine: Self-Refinement of Parallel Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-learning-refine-self-refinement-parallel/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qibin Wang, Pu Zhao, Shaohan Huang, et al.*2026*
782. **[Learning Uncertainty from Sequential Internal Dispersion in Large Language Models](https://md.research.elamur.ai/free/en/papers/srey-2026-learning-uncertainty-sequential-internal-dispersion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ponhvoan Srey, Xiaobao Wu, Cong-Duy T Nguyen, et al.*2026*
783. **[LeLoRA: Learnable Low-Rank Adaptation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-lelora-learnable-low-rank-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoling Zhou, Mingjie Zhang, Zhemg Lee, et al.*2026*
784. **[LEPO: Latent Reasoning Policy Optimization for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-lepo-latent-reasoning-policy-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuyan Zhou, Jiarui Yu, Hande Dong, et al.*2026*
785. **[MARD: Module-Aware Reasoning Distillation for Language Models with Adaptive Supervision](https://md.research.elamur.ai/free/en/papers/yang-2026-mard-module-aware-reasoning-distillation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqi Yang, Jianjun Li, Zhibo Zhang, et al.*2026*
786. **[MATH-IDN: A Multilingual Mathematical Problem Solving Dataset Featuring Local Languages in Indonesia](https://md.research.elamur.ai/free/en/papers/xiao-2026-math-idn-multilingual-mathematical-problem/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiao Xiao, Iftitahu Ni'mah, Yuyun Wabula, et al.*2026*
787. **[MathSight: A Benchmark Exploring Have Vision-Language Models Really Seen in University-Level Mathematical Reasoning?](https://md.research.elamur.ai/free/en/papers/wang-2026-mathsight-benchmark-exploring-have-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuandong Wang, Yao Cui, Yuxin Zhao, et al.*2026*
788. **[MAXS: Meta-Adaptive Exploration with LLM Agents](https://md.research.elamur.ai/free/en/papers/zhang-2026-maxs-meta-adaptive-exploration-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jian Zhang, Zhiyuan Wang, Zhangqi Wang, et al.*2026*
789. **[Merlin's Whisper: Enabling Efficient Reasoning in Large Language Models via Black-box Persuasive Prompting](https://md.research.elamur.ai/free/en/papers/xia-2026-merlin-s-whisper-enabling-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Heming Xia, Cunxiao Du, Rui Li, et al.*2026*
790. **[Mixture of Heterogeneous Grouped Experts for Language Modeling](https://md.research.elamur.ai/free/en/papers/ma-2026-mixture-heterogeneous-grouped-experts-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhicheng Ma, Xiang Liu, Zhaoxiang Liu, et al.*2026*
791. **[Multi-Constraint State Tracking with Negation: A Diagnostic Benchmark for LLM World Modeling](https://md.research.elamur.ai/free/en/papers/sar-2026-multi-constraint-state-tracking-negation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ayan Sar, Pranav Singh Puri, Sumit Aich, et al.*2026*
792. **[Multimodal LLMs Do Not Compose Skills Optimally across Modalities](https://md.research.elamur.ai/free/en/papers/ontalvilla-2026-multimodal-llms-do-not-compose/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune*2026*
793. **[N-GRPO: Embedding-Level Neighbor Mixing for Enhanced Policy Optimization](https://md.research.elamur.ai/free/en/papers/zhu-2026-n-grpo-embedding-level-neighbor/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xukun Zhu, Hang Yu, Peng Di, et al.*2026*
794. **[NeuralFSM: Adaptive Multi-Agent Coordination via Learning Finite-State Execution Policy](https://md.research.elamur.ai/free/en/papers/wang-2026-neuralfsm-adaptive-multi-agent-coordination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiye Wang, Yu Wang, Jianbin Li, et al.*2026*
795. **[Open Problems Solved by LLMs? A Survey of Verifiable Mathematical Discovery](https://md.research.elamur.ai/free/en/papers/tzachristas-2026-open-problems-solved-llms-survey/) [Big Picture v2: Crafting a Research Narrative](https://md.research.elamur.ai/free/en/venues/bigpicture/)**Ioannis Tzachristas, Georgios Tzachristas, Aifen Sui*2026*
796. **[PAM: Enhancing General Alignment of Large Reasoning Models through Priority-Aware Metacognition](https://md.research.elamur.ai/free/en/papers/xu-2026-pam-enhancing-general-alignment-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhihao Xu, Fuzhen Yang, Liang Lin, et al.*2026*
797. **[Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow](https://md.research.elamur.ai/free/en/papers/zhong-2026-parallelism-generation-order-masked-diffusion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangyang Zhong, Yanmei Gu, Zhengqing Zang, et al.*2026*
798. **[PILOT: Planning via Internalized Latent Optimization Trajectories for Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-pilot-planning-internalized-latent-optimization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoyu Zheng, Yun Zhu, Yuqian Yuan, et al.*2026*
799. **[Policy-Guided Stepwise Action Planning for Controllable LLM Reasoning](https://md.research.elamur.ai/free/en/papers/zhou-2026-policy-guided-stepwise-action-planning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianpeng Zhou, Qisheng Hu, Jiahai Wang, et al.*2026*
800. **[Program-of-Thought Reveals LLM Abstraction Ceilings](https://md.research.elamur.ai/free/en/papers/zhou-2026-program-thought-reveals-llm-abstraction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mike Zhou, Fenil Bardoliya, Vivek Gupta, et al.*2026*

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