---
title: "Who cites Lukas Blecher — page 6 — 7,145 papers of our library"
description: "7,145 papers of the Elamur Research library cite the works of Lukas Blecher, found in their bibliographies · page 6 of 15 · 501–600; the most…"
canonical: "https://research.elamur.ai/free/en/authors/lukas-blecher/cited-by/page/6/"
---
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# Who cites Lukas Blecher

7,156 citations of their works from 7,145 papers of our library (of the 149,439 whose bibliographies we read) · 1,417 with a page here, the most cited first · page 6 of 15 · 501–600 · [← Lukas Blecher](https://md.research.elamur.ai/free/en/authors/lukas-blecher/)

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501. **[MART: Improving LLM Safety with Multi-round Automatic Red-Teaming](https://md.research.elamur.ai/free/en/papers/ge-2024-mart-improving-llm-safety-multi/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Suyu Ge, Chunting Zhou, Rui Hou, et al.*2024 · 82 citations*
502. [**Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive arXiv:2402.13228**Arka Pal, Deep Karkhanis, Samuel Dooley, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/pal-2024-smaug-fixing-failure-modes-preference/)
503. [**TableLlama: Towards Open Large Generalist Models for Tables arXiv:2311.09206**Tianshu Zhang, Xiang Yue, Yifei Li, et al.*2023 · 82 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-tablellama-towards-open-large-generalist/)
504. **[In-Context Learning with Long-Context Models: An In-Depth Exploration](https://md.research.elamur.ai/free/en/papers/bertsch-2025-context-learning-long-context-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Amanda Bertsch, Maor Ivgi, Emily Xiao, et al.*2025 · 81 citations*
505. [**LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning arXiv:2401.01325**Hongye Jin, Xiaotian Han, Jingfeng Yang, et al.*2024 · 81 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-llm-maybe-longlm-self-extend/)
506. **[You Only Look at Screens: Multimodal Chain-of-Action Agents](https://md.research.elamur.ai/free/en/papers/zhang-2024-you-only-look-screens-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuosheng Zhang, Aston Zhang*2024 · 81 citations*
507. [**In-Context Unlearning: Language Models as Few Shot Unlearners arXiv:2310.07579**Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/pawelczyk-2023-context-unlearning-language-models-few/)
508. [**MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use arXiv:2310.03128**Yue Huang, Jiawen Shi, Yuan Li, et al.*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-metatool-benchmark-large-language-models/)
509. [**Punica: Multi-Tenant LoRA Serving MLSys 2024**Lequn Chen, Zihao Ye, Yongji Wu, et al.*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-punica-multi-tenant-lora-serving/)
510. [**RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models arXiv:2309.15088**Ronak Pradeep, Sahel Sharifymoghaddam, Jimmy Lin*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/pradeep-2023-rankvicuna-zero-shot-listwise-document/)
511. [**Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention arXiv:2404.07143**Tsendsuren Munkhdalai, Manaal Faruqui, Siddharth Gopal*2024 · 80 citations*](https://md.research.elamur.ai/free/en/papers/munkhdalai-2024-leave-no-context-behind-efficient/)
512. [**Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoning arXiv:2410.14211**Xingyu Tan, Xiaoyang Wang, Qing Liu, et al.*2024 · 80 citations*](https://md.research.elamur.ai/free/en/papers/tan-2024-paths-over-graph-knowledge-graph/)
513. [**PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models arXiv:2402.07867**Wei Zou, Runpeng Geng, Binghui Wang, et al.*2024 · 80 citations*](https://md.research.elamur.ai/free/en/papers/zou-2024-poisonedrag-knowledge-corruption-attacks-retrieval/)
514. **[Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing](https://md.research.elamur.ai/free/en/papers/tian-2024-toward-self-improvement-llms-imagination/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ye Tian, Baolin Peng, Linfeng Song, et al.*2024 · 80 citations*
515. [**S-LoRA: Serving Thousands of Concurrent LoRA Adapters MLSys 2024**Ying Sheng, Shiyi Cao, Dacheng Li, et al.*2023 · 80 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2023-s-lora-serving-thousands-concurrent/)
516. **[AutoRE: Document-Level Relation Extraction with Large Language Models](https://md.research.elamur.ai/free/en/papers/xue-2024-autore-document-level-relation-extraction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lilong Xue, Dan Zhang, Yuxiao Dong, et al.*2024 · 79 citations*
517. [**Common 7B Language Models Already Possess Strong Math Capabilities arXiv:2403.04706**Chen Li, Weiqi Wang, Jingcheng Hu, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-common-7b-language-models-already/)
518. **[Making Reasoning Matter: Measuring and Improving Faithfulness of Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/paul-2024-making-reasoning-matter-measuring-improving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Debjit Paul, Robert West, Antoine Bosselut, et al.*2024 · 79 citations*
519. [**Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities arXiv:2408.07666**Enneng Yang, Li Shen, Guibing Guo, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-model-merging-llms-mllms-methods/)
520. [**Tuning Language Models by Proxy arXiv:2401.08565**Alisa Liu, Xiaochuang Han, Yizhong Wang, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-tuning-language-models-proxy/)
521. [**LEGO-Prover: Neural Theorem Proving with Growing Libraries arXiv:2310.00656**Haiming Wang, Huajian Xin, Chuanyang Zheng, et al.*2023 · 79 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-lego-prover-neural-theorem-proving/)
522. **[KG-Agent: An Efficient Autonomous Agent Framework for Complex Reasoning over Knowledge Graph](https://md.research.elamur.ai/free/en/papers/jiang-2025-kg-agent-efficient-autonomous-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinhao Jiang, Kun Zhou, Wayne Xin Zhao, et al.*2025 · 78 citations*
523. [**Humans or LLMs as the Judge? A Study on Judgement Biases arXiv:2402.10669**Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.*2024 · 78 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-humans-llms-judge-study-judgement/)
524. [**LLaMA Beyond English: An Empirical Study on Language Capability Transfer arXiv:2401.01055**Jun Zhao, Zhihao Zhang, Luhui Gao, et al.*2024 · 78 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-llama-english-empirical-study-language/)
525. **[Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps](https://md.research.elamur.ai/free/en/papers/chuang-2024-lookback-lens-detecting-mitigating-contextual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yung-Sung Chuang, Linlu Qiu, Cheng-Yu Hsieh, et al.*2024 · 78 citations*
526. **[Multilingual Instruction Tuning With Just a Pinch of Multilinguality](https://md.research.elamur.ai/free/en/papers/shaham-2024-multilingual-instruction-tuning-just-pinch/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Uri Shaham, Jonathan Herzig, Roee Aharoni, et al.*2024 · 78 citations*
527. [**Are Multilingual LLMs Culturally-Diverse Reasoners? An Investigation into Multicultural Proverbs and Sayings arXiv:2309.08591**Chen Cecilia Liu, Fajri Koto, Timothy Baldwin, et al.*2023 · 78 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-multilingual-llms-culturally-diverse-reasoners/)
528. [**Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs arXiv:2308.13387**Yuxia Wang, Haonan Li, Xudong Han, et al.*2023 · 78 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-answer-dataset-evaluating-safeguards-llms/)
529. **[Factuality of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/wang-2024-factuality-large-language-models-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuxia Wang, Minghan Wang, Muhammad Arslan Manzoor, et al.*2024 · 77 citations*
530. **[LexEval: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-lexeval-comprehensive-chinese-legal-benchmark/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Haitao Li, You Chen, Qingyao Ai, et al.*2024 · 77 citations*
531. [**SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling arXiv:2312.15166**Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-solar-10-7b-scaling-large/)
532. **[KMMLU: Measuring Massive Multitask Language Understanding in Korean](https://md.research.elamur.ai/free/en/papers/son-2025-kmmlu-measuring-massive-multitask-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guijin Son, Hanwool Lee, Sungdong Kim, et al.*2025 · 76 citations*
533. [**Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model Evaluators arXiv:2403.16950**Yinhong Liu, Han Zhou, Zhijiang Guo, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-aligning-human-judgement-role-pairwise/)
534. **[Measuring Political Bias in Large Language Models: What Is Said and How It Is Said](https://md.research.elamur.ai/free/en/papers/bang-2024-measuring-political-bias-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yejin Bang, Delong Chen, Nayeon Lee, et al.*2024 · 76 citations*
535. [**OR-Bench: An Over-Refusal Benchmark for Large Language Models arXiv:2405.20947**Justin Cui, Wei-Lin Chiang, Ion Stoica, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/cui-2024-bench-over-refusal-benchmark-large/)
536. [**Self-Preference Bias in LLM-as-a-Judge arXiv:2410.21819**Koki Wataoka, Tsubasa Takahashi, Ryokan Ri*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/wataoka-2024-self-preference-bias-llm-judge/)
537. [**Self-Reflection in LLM Agents: Effects on Problem-Solving Performance arXiv:2405.06682 · 2nd International Conference on Foundation and Large Language Models (FLLM 2024), pp. 476-483**Matthew Renze, Erhan Guven*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/renze-2024-self-reflection-llm-agents-effects/)
538. **[Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions](https://md.research.elamur.ai/free/en/papers/chen-2025-benchmarking-large-language-models-answering/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hanjie Chen, Zhouxiang Fang, Yash Singla, et al.*2025 · 75 citations*
539. **[Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training](https://md.research.elamur.ai/free/en/papers/fang-2024-enhancing-noise-robustness-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Feiteng Fang, Yuelin Bai, Shiwen Ni, et al.*2024 · 75 citations*
540. [**Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers arXiv:2404.04925**Libo Qin, Qiguang Chen, Yuhang Zhou, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-multilingual-large-language-model-survey/)
541. [**PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities**Settaluri Sravanthi, Meet Doshi, Pavan Tankala, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/sravanthi-2024-pub-pragmatics-understanding-benchmark-assessing/)
542. **[Self-Contrast: Better Reflection Through Inconsistent Solving Perspectives](https://md.research.elamur.ai/free/en/papers/zhang-2024-self-contrast-better-reflection-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqi Zhang, Yongliang Shen, Linjuan Wu, et al.*2024 · 75 citations*
543. **[Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions](https://md.research.elamur.ai/free/en/papers/masoud-2025-cultural-alignment-large-language-models/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Reem I. Masoud, Ziquan Liu, Martin Ferianc, et al.*2025 · 74 citations*
544. **[MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning](https://md.research.elamur.ai/free/en/papers/li-2024-mediq-question-asking-llms-benchmark/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, et al.*2024 · 74 citations*
545. [**QuRating: Selecting High-Quality Data for Training Language Models arXiv:2402.09739**Alexander Wettig, Aatmik Gupta, Saumya Malik, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/wettig-2024-qurating-selecting-high-quality-data/)
546. **[ReFT: Representation Finetuning for Language Models](https://md.research.elamur.ai/free/en/papers/wu-2024-reft-representation-finetuning-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhengxuan Wu, Aryaman Arora, Zheng Wang, et al.*2024 · 74 citations*
547. **[SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration](https://md.research.elamur.ai/free/en/papers/zhang-2024-sageattention-accurate-8-bit-attention/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Jintao Zhang, Jia Wei, Haofeng Huang, et al.*2024 · 74 citations*
548. [**When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards arXiv:2402.01781**Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/alzahrani-2024-benchmarks-targets-revealing-sensitivity-large/)
549. **[MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning](https://md.research.elamur.ai/free/en/papers/sprague-2023-musr-testing-limits-chain-thought/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Zayne Sprague, Xi Ye, Kaj Bostrom, et al.*2023 · 74 citations*
550. [**Benchmarking Benchmark Leakage in Large Language Models arXiv:2404.18824**Ruijie Xu, Zengzhi Wang, Run-Ze Fan, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/)
551. [**Repetition Improves Language Model Embeddings arXiv:2402.15449**Jacob Mitchell Springer, Suhas Kotha, Daniel Fried, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/springer-2024-repetition-improves-language-model-embeddings/)
552. [**A Primer on the Inner Workings of Transformer-based Language Models arXiv:2405.00208**Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ferrando-2024-primer-inner-workings-transformer-based/)
553. **[Black-Box Prompt Optimization: Aligning Large Language Models without Model Training](https://md.research.elamur.ai/free/en/papers/cheng-2024-black-box-prompt-optimization-aligning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiale Cheng, Xiao Liu, Kehan Zheng, et al.*2024 · 72 citations*
554. **[HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM](https://md.research.elamur.ai/free/en/papers/wang-2024-helpsteer-multi-attribute-helpfulness-dataset/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zhilin Wang, Yi Dong, Jiaqi Zeng, et al.*2024 · 72 citations*
555. [**Secrets of RLHF in Large Language Models Part II: Reward Modeling arXiv:2401.06080**Binghai Wang, Rui Zheng, Lu Chen, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-secrets-rlhf-large-language-models/)
556. **[Towards Safer Large Language Models through Machine Unlearning](https://md.research.elamur.ai/free/en/papers/liu-2024-safer-large-language-models-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, et al.*2024 · 72 citations*
557. [**Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation arXiv:2307.15337**Xuefei Ning, Zinan Lin, Zixuan Zhou, et al.*2023 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ning-2023-skeleton-thought-prompting-llms-efficient/)
558. [**The Unreasonable Ineffectiveness of the Deeper Layers arXiv:2403.17887**Andrey Gromov, Kushal Tirumala, Hassan Shapourian, et al.*2024 · 71 citations*](https://md.research.elamur.ai/free/en/papers/gromov-2024-unreasonable-ineffectiveness-deeper-layers/)
559. **[Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks](https://md.research.elamur.ai/free/en/papers/kang-2023-knowledge-augmented-reasoning-distillation-small/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Minki Kang, Seanie Lee, Jinheon Baek, et al.*2023 · 71 citations*
560. **[IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models](https://md.research.elamur.ai/free/en/papers/adelani-2025-irokobench-new-benchmark-african-languages/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**David Ifeoluwa Adelani, Jessica Ojo, Israel Abebe Azime, et al.*2025 · 70 citations*
561. **[Aligning Large and Small Language Models via Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/ranaldi-2024-aligning-large-small-language-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Leonardo Ranaldi, Andre Freitas*2024 · 70 citations*
562. **[MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark](https://md.research.elamur.ai/free/en/papers/liu-2024-mathbench-evaluating-theory-application-proficiency/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongwei Liu, Zilong Zheng, Yuxuan Qiao, et al.*2024 · 70 citations*
563. **[Tug-of-War between Knowledge: Exploring and Resolving Knowledge Conflicts in Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/jin-2024-tug-war-between-knowledge-exploring/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zhuoran Jin, Pengfei Cao, Yubo Chen, et al.*2024 · 70 citations*
564. **[Recent Advances in Speech Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/cui-2025-recent-advances-speech-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqian Cui, Dianzhi Yu, Xiaoqi Jiao, et al.*2025 · 69 citations*
565. **[Aligner: Efficient Alignment by Learning to Correct](https://md.research.elamur.ai/free/en/papers/ji-2024-aligner-efficient-alignment-learning-correct/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaming Ji, Boyuan Chen, Hantao Lou, et al.*2024 · 69 citations*
566. **[Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2024-self-alignment-factuality-mitigating-hallucinations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoying Zhang, Baolin Peng, Ye Tian, et al.*2024 · 69 citations*
567. [**CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation arXiv:2311.18702**Pei Ke, Bosi Wen, Zhuoer Feng, et al.*2023 · 69 citations*](https://md.research.elamur.ai/free/en/papers/ke-2023-critiquellm-informative-critique-generation/)
568. **[Apertus: Democratizing Open and Compliant LLMs for Global Language Environments](https://md.research.elamur.ai/free/en/papers/cano-2026-apertus-democratizing-open-compliant-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.*2026 · 68 citations*
569. **[A Thorough Examination of Decoding Methods in the Era of LLMs](https://md.research.elamur.ai/free/en/papers/shi-2024-thorough-examination-decoding-methods-era/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chufan Shi, Haoran Yang, Deng Cai, et al.*2024 · 68 citations*
570. [**Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents arXiv:2408.07199**Pranav Putta, Edmund Mills, Naman Garg, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/putta-2024-agent-q-advanced-reasoning-learning/)
571. **[Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards](https://md.research.elamur.ai/free/en/papers/wang-2024-arithmetic-control-llms-diverse-user/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoxiang Wang, Yong Lin, Wei Xiong, et al.*2024 · 68 citations*
572. **[KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction](https://md.research.elamur.ai/free/en/papers/li-2024-knowcoder-coding-structured-knowledge-into/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zixuan Li, Yutao Zeng, Yuxin Zuo, et al.*2024 · 68 citations*
573. [**MagicPIG: LSH Sampling for Efficient LLM Generation arXiv:2410.16179**Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-magicpig-lsh-sampling-efficient-llm/)
574. **[Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration](https://md.research.elamur.ai/free/en/papers/feng-2024-modular-pluralism-pluralistic-alignment-multi/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shangbin Feng, Taylor Sorensen, Yuhan Liu, et al.*2024 · 68 citations*
575. [**Branch-Solve-Merge Improves Large Language Model Evaluation and Generation arXiv:2310.15123**Swarnadeep Saha, Omer Levy, Asli Celikyilmaz, et al.*2023 · 68 citations*](https://md.research.elamur.ai/free/en/papers/saha-2023-branch-solve-merge-improves-large/)
576. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/)
577. [**An Empirical Study of Mamba-based Language Models arXiv:2406.07887**Roger Waleffe, Wonmin Byeon, Duncan Riach, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/waleffe-2024-empirical-study-mamba-based-language/)
578. **[Are Large Language Models Capable of Generating Human-Level Narratives?](https://md.research.elamur.ai/free/en/papers/tian-2024-are-large-language-models-capable/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yufei Tian, Tenghao Huang, Miri Liu, et al.*2024 · 67 citations*
579. **[Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2024-buffer-thoughts-thought-augmented-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ling Yang, Zhaochen Yu, Tianjun Zhang, et al.*2024 · 67 citations*
580. [**FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion arXiv:2406.06858**Li-Wen Chang, Wenlei Bao, Qi Hou, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/chang-2024-flux-fast-software-based-communication/)
581. **[Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue](https://md.research.elamur.ai/free/en/papers/gu-2024-model-editing-harms-general-abilities/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jia-Chen Gu, Hao-Xiang Xu, Jun-Yu Ma, et al.*2024 · 67 citations*
582. **[MT-Eval: A Multi-Turn Capabilities Evaluation Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/kwan-2024-mt-eval-multi-turn-capabilities/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wai-Chung Kwan, Xingshan Zeng, Yuxin Jiang, et al.*2024 · 67 citations*
583. **[OffsetBias: Leveraging Debiased Data for Tuning Evaluators](https://md.research.elamur.ai/free/en/papers/park-2024-offsetbias-leveraging-debiased-data-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junsoo Park, Seungyeon Jwa, Ren Meiying, et al.*2024 · 67 citations*
584. **[On Context Utilization in Summarization with Large Language Models](https://md.research.elamur.ai/free/en/papers/ravaut-2024-context-utilization-summarization-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mathieu Ravaut, Aixin Sun, Nancy Chen, et al.*2024 · 67 citations*
585. [**AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation arXiv:2311.07397**Junyang Wang, Yuhang Wang, Guohai Xu, et al.*2023 · 67 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-amber-llm-free-multi-dimensional/)
586. [**Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications arXiv:2402.05162**Boyi Wei, Kaixuan Huang, Yangsibo Huang, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/wei-2024-assessing-brittleness-safety-alignment-pruning/)
587. **[C3oT: Generating Shorter Chain-of-Thought without Compromising Effectiveness](https://md.research.elamur.ai/free/en/papers/kang-2024-c3ot-generating-shorter-chain-thought/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yu Kang, Xianghui Sun, Liangyu Chen, et al.*2024 · 66 citations*
588. [**JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks arXiv:2404.03027**Weidi Luo, Siyuan Ma, Xiaogeng Liu, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/luo-2024-jailbreakv-benchmark-assessing-robustness-multimodal/)
589. **[Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models](https://md.research.elamur.ai/free/en/papers/amayuelas-2024-knowledge-knowledge-exploring-known-unknowns/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alfonso Amayuelas, Kyle Wong, Liangming Pan, et al.*2024 · 66 citations*
590. [**Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models arXiv:2311.08692**Keming Lu, Hongyi Yuan, Runji Lin, et al.*2023 · 66 citations*](https://md.research.elamur.ai/free/en/papers/lu-2023-routing-expert-efficient-reward-guided/)
591. **[MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/chang-2025-main-rag-multi-agent-filtering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chia-Yuan Chang, Zhimeng Jiang, Vineeth Rakesh, et al.*2025 · 65 citations*
592. **[On the Multilingual Ability of Decoder-based Pre-trained Language Models: Finding and Controlling Language-Specific Neurons](https://md.research.elamur.ai/free/en/papers/kojima-2024-multilingual-ability-decoder-based-pre/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Takeshi Kojima, Itsuki Okimura, Yusuke Iwasawa, et al.*2024 · 65 citations*
593. **[Small LLMs Are Weak Tool Learners: A Multi-LLM Agent](https://md.research.elamur.ai/free/en/papers/shen-2024-small-llms-are-weak-tool/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weizhou Shen, Chenliang Li, Hongzhan Chen, et al.*2024 · 65 citations*
594. [**Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models arXiv:2402.13064**Haoran Li, Qingxiu Dong, Zhengyang Tang, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-synthetic-data-almost-scratch-generalized/)
595. [**We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning? arXiv:2407.01284**Runqi Qiao, Qiuna Tan, Guanting Dong, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2024-math-large-multimodal-model-achieve/)
596. [**Layer by Layer: Uncovering Hidden Representations in Language Models arXiv:2502.02013**Oscar Skean, Md Rifat Arefin, Dan Zhao, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/skean-2025-layer-layer-uncovering-hidden-representations/)
597. **[Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge](https://md.research.elamur.ai/free/en/papers/wu-2025-meta-rewarding-language-models-self/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianhao Wu, Weizhe Yuan, Olga Golovneva, et al.*2025 · 64 citations*
598. **[SpiRit-LM: Interleaved Spoken and Written Language Model](https://md.research.elamur.ai/free/en/papers/nguyen-2025-spirit-lm-interleaved-spoken-written/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tu Anh Nguyen, Benjamin Muller, Bokai Yu, et al.*2025 · 64 citations*
599. **[Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2024-agent-flan-designing-data-methods/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zehui Chen, Kuikun Liu, Qiuchen Wang, et al.*2024 · 64 citations*
600. [**Evaluation of OpenAI o1: Opportunities and Challenges of AGI arXiv:2409.18486**Tianyang Zhong, Zhengliang Liu, Yi Pan, et al.*2024 · 64 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-evaluation-openai-o1-opportunities-challenges/)

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