---
title: "Who cites Itai Gat — 1,020 papers of our library"
description: "1,020 papers of the Elamur Research library cite the works of Itai Gat, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/itai-gat/cited-by/"
---
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# Who cites Itai Gat

1,023 citations of their works from 1,020 papers of our library (of the 141,840 whose bibliographies we read) · 88 with a page here, the most cited first · [← Itai Gat](https://md.research.elamur.ai/free/en/authors/itai-gat/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,863 citations*
2. [**Qwen Technical Report arXiv:2309.16609**Jinze Bai, Shuai Bai, Yunfei Chu, et al.*2023 · 1,645 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-technical-report/)
3. **[Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/liu-2023-your-code-generated-chatgpt-really/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiawei Liu, Chunqiu Steven Xia, Yuyao Wang, et al.*2023 · 632 citations*
4. [**SWE-bench: Can Language Models Resolve Real-World GitHub Issues? arXiv:2310.06770**Carlos E. Jimenez, John Yang, Alexander Wettig, et al.*2024 · 617 citations*](https://md.research.elamur.ai/free/en/papers/jimenez-2024-swe-bench-can-language-models/)
5. [**MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework arXiv:2308.00352**Sirui Hong, Mingchen Zhuge, Jiaqi Chen, et al.*2023 · 615 citations*](https://md.research.elamur.ai/free/en/papers/hong-2023-metagpt-meta-programming-multi/)
6. [**HybridFlow: A Flexible and Efficient RLHF Framework arXiv:2409.19256**Guangming Sheng, Chi Zhang, Zilingfeng Ye, et al.*2024 · 598 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2024-hybridflow-flexible-efficient-rlhf-framework/)
7. [**MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models arXiv:2309.12284**Longhui Yu, Weisen Jiang, Han Shi, et al.*2023 · 556 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-metamath-bootstrap-your-own-mathematical/)
8. [**Qwen2.5-Coder Technical Report arXiv:2409.12186**Binyuan Hui, Jian Yang, Zeyu Cui, et al.*2024 · 547 citations*](https://md.research.elamur.ai/free/en/papers/hui-2024-qwen2-5-coder-technical-report/)
9. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 540 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
10. [**Jailbreaking Black Box Large Language Models in Twenty Queries arXiv:2310.08419**Patrick Chao, Alexander Robey, Edgar Dobriban, et al.*2023 · 533 citations*](https://md.research.elamur.ai/free/en/papers/chao-2023-jailbreaking-black-box-large-language/)
11. [**Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation arXiv:2308.15363**Dawei Gao, Haibin Wang, Yaliang Li, et al.*2023 · 461 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-text-sql-empowered-large-language/)
12. [**The Falcon Series of Open Language Models arXiv:2311.16867**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 436 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
13. **[Improving Text Embeddings with Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-improving-text-embeddings-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liang Wang, Nan Yang, Xiaolong Huang, et al.*2024 · 433 citations*
14. [**AgentBench: Evaluating LLMs as Agents arXiv:2308.03688**Xiao Liu, Hao Yu, Hanchen Zhang, et al.*2023 · 405 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-agentbench-evaluating-llms-agents/)
15. [**A Survey on Large Language Models for Code Generation arXiv:2406.00515**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 366 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
16. [**Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! arXiv:2310.03693**Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.*2023 · 331 citations*](https://md.research.elamur.ai/free/en/papers/qi-2023-fine-tuning-aligned-language-models/)
17. [**MEDITRON-70B: Scaling Medical Pretraining for Large Language Models arXiv:2311.16079**Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.*2023 · 311 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-meditron-70b-scaling-medical-pretraining/)
18. [**InternLM2 Technical Report arXiv:2403.17297**Zheng Cai, Maosong Cao, Haojiong Chen, et al.*2024 · 299 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-internlm2-technical-report/)
19. [**MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning arXiv:2309.05653**Xiang Yue, Xingwei Qu, Ge Zhang, et al.*2023 · 288 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mammoth-building-math-generalist-models/)
20. **[Large Language Models for Mathematical Reasoning: Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/ahn-2024-large-language-models-mathematical-reasoning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Janice Ahn, Rishu Verma, Renze Lou, et al.*2024 · 279 citations*
21. [**Llemma: An Open Language Model For Mathematics arXiv:2310.10631**Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.*2023 · 276 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-llemma-open-language-model-mathematics/)
22. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 259 citations*
23. [**Large Language Monkeys: Scaling Inference Compute with Repeated Sampling arXiv:2407.21787**Bradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.*2024 · 241 citations*](https://md.research.elamur.ai/free/en/papers/brown-2024-large-language-monkeys-scaling-inference/)
24. [**LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset arXiv:2309.11998**Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.*2023 · 236 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-lmsys-chat-1m-large-scale/)
25. [**Tower: An Open Multilingual Large Language Model for Translation-Related Tasks arXiv:2402.17733**Duarte M. Alves, Jose Pombal, Nuno M. Guerreiro, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/alves-2024-tower-open-multilingual-large-language/)
26. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
27. [**ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving arXiv:2309.17452**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 222 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-tora-tool-integrated-reasoning-agent/)
28. [**Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch arXiv:2311.03099**Le Yu, Bowen Yu, Haiyang Yu, et al.*2023 · 210 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-language-models-super-mario-absorbing/)
29. [**Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2 arXiv:2311.10702**Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.*2023 · 199 citations*](https://md.research.elamur.ai/free/en/papers/ivison-2023-camels-changing-climate-enhancing-lm/)
30. **[Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset](https://md.research.elamur.ai/free/en/papers/wang-2024-measuring-multimodal-mathematical-reasoning-math/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ke Wang, Junting Pan, Weikang Shi, et al.*2024 · 198 citations*
31. [**DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence arXiv:2406.11931**DeepSeek-AI, Qihao Zhu, Daya Guo, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2024-deepseek-coder-v2-breaking-barrier/)
32. **[GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer](https://md.research.elamur.ai/free/en/papers/zaratiana-2024-gliner-generalist-model-named-entity/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Urchade Zaratiana, Nadi Tomeh, Pierre Holat, et al.*2024 · 189 citations*
33. **[Adapting Language Models to Compress Contexts](https://md.research.elamur.ai/free/en/papers/chevalier-2023-adapting-language-models-compress-contexts/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Alexis Chevalier, Alexander Wettig, Anirudh Ajith, et al.*2023 · 179 citations*
34. [**Effective Long-Context Scaling of Foundation Models arXiv:2309.16039**Wenhan Xiong, Jingyu Liu, Igor Molybog, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-effective-long-context-scaling-foundation/)
35. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 174 citations*
36. [**SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language Model arXiv:2502.02737**Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.*2025 · 171 citations*](https://md.research.elamur.ai/free/en/papers/allal-2025-smollm2-smol-goes-big-data/)
37. [**BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions arXiv:2406.15877**Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-bigcodebench-benchmarking-code-generation-diverse/)
38. [**Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models arXiv:2410.07985**Bofei Gao, Feifan Song, Zhe Yang, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-omni-math-universal-olympiad-level/)
39. **[LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding](https://md.research.elamur.ai/free/en/papers/elhoushi-2024-layerskip-enabling-early-exit-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, et al.*2024 · 155 citations*
40. [**Moshi: a speech-text foundation model for real-time dialogue arXiv:2410.00037**Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.*2024 · 154 citations*](https://md.research.elamur.ai/free/en/papers/defossez-2024-moshi-speech-text-foundation-model/)
41. [**PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling arXiv:2406.02069**Zefan Cai, Yichi Zhang, Bofei Gao, et al.*2024 · 151 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-pyramidkv-dynamic-kv-cache-compression/)
42. **[CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges](https://md.research.elamur.ai/free/en/papers/zhang-2024-codeagent-enhancing-code-generation-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kechi Zhang, Jia Li, Ge Li, et al.*2024 · 147 citations*
43. **[Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2024-draft-verify-lossless-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jun Zhang, Jue Wang, Huan Li, et al.*2024 · 146 citations*
44. [**LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens arXiv:2402.13753**Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, et al.*2024 · 139 citations*](https://md.research.elamur.ai/free/en/papers/ding-2024-longrope-extending-llm-context/)
45. [**MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback arXiv:2309.10691**Xingyao Wang, Zihan Wang, Jiateng Liu, et al.*2023 · 137 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-mint-evaluating-llms-multi-turn/)
46. [**Long-context LLMs Struggle with Long In-context Learning arXiv:2404.02060**Tianle Li, Ge Zhang, Quy Duc Do, et al.*2024 · 132 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-long-context-llms-struggle-long/)
47. **[ReFT: Reasoning with Reinforced Fine-Tuning](https://md.research.elamur.ai/free/en/papers/trung-2024-reft-reasoning-reinforced-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luong Trung, Xinbo Zhang, Zhanming Jie, et al.*2024 · 131 citations*
48. **[A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems](https://md.research.elamur.ai/free/en/papers/yi-2024-survey-recent-advances-llm-based/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Zihao Yi, Jiarui Ouyang, Zhe Xu, et al.*2024 · 129 citations*
49. [**Chameleon: Mixed-Modal Early-Fusion Foundation Models arXiv:2405.09818**Chameleon Team*2024 · 117 citations*](https://md.research.elamur.ai/free/en/papers/team-2024-chameleon-mixed-modal-early-fusion/)
50. [**QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks arXiv:2402.04396**Albert Tseng, Jerry Chee, Qingyao Sun, et al.*2024 · 116 citations*](https://md.research.elamur.ai/free/en/papers/tseng-2024-quip-even-better-llm-quantization/)
51. [**Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities arXiv:2404.17790**Kazuki Fujii, Taishi Nakamura, Mengsay Loem, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/fujii-2024-continual-pre-training-cross-lingual/)
52. [**GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction arXiv:2310.03668**Oscar Sainz, Iker Garcia-Ferrero, Rodrigo Agerri, et al.*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/sainz-2023-gollie-annotation-guidelines-improve-zero/)
53. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
54. [**Break the Sequential Dependency of LLM Inference Using Lookahead Decoding arXiv:2402.02057**Yichao Fu, Peter Bailis, Ion Stoica, et al.*2024 · 112 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-break-sequential-dependency-llm-inference/)
55. [**V-STaR: Training Verifiers for Self-Taught Reasoners arXiv:2402.06457**Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-2024-v-star-training-verifiers-self/)
56. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 109 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
57. **[GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers](https://md.research.elamur.ai/free/en/papers/li-2024-gsm-plus-comprehensive-benchmark-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qintong Li, Leyang Cui, Xueliang Zhao, et al.*2024 · 107 citations*
58. [**Arcee's MergeKit: A Toolkit for Merging Large Language Models arXiv:2403.13257**Charles Goddard, Shamane Siriwardhana, Malikeh Ehghaghi, et al.*2024 · 101 citations*](https://md.research.elamur.ai/free/en/papers/goddard-2024-arcee-s-mergekit-toolkit-merging/)
59. [**MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning arXiv:2310.03731**Ke Wang, Houxing Ren, Aojun Zhou, et al.*2023 · 98 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-mathcoder-seamless-code-integration-llms/)
60. [**FireAct: Toward Language Agent Fine-tuning arXiv:2310.05915**Baian Chen, Chang Shu, Ehsan Shareghi, et al.*2023 · 96 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-fireact-toward-language-agent-fine/)
61. **[PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM Inference](https://md.research.elamur.ai/free/en/papers/yang-2024-pyramidinfer-pyramid-kv-cache-compression/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dongjie Yang, Xiaodong Han, Yan Gao, et al.*2024 · 91 citations*
62. [**Skywork: A More Open Bilingual Foundation Model arXiv:2310.19341**Tianwen Wei, Liang Zhao, Lichang Zhang, et al.*2023 · 91 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-skywork-more-open-bilingual/)
63. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
64. [**CodeGemma: Open Code Models Based on Gemma arXiv:2406.11409**CodeGemma Team: Heri Zhao, Jeffrey Hui, Joshua Howland, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-codegemma-open-code-models-based/)
65. **[OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models](https://md.research.elamur.ai/free/en/papers/huang-2025-opencoder-open-cookbook-top-tier/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siming Huang, Tianhao Cheng, Jason Klein Liu, et al.*2025 · 81 citations*
66. [**LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning arXiv:2401.01325**Hongye Jin, Xiaotian Han, Jingfeng Yang, et al.*2024 · 78 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-llm-maybe-longlm-self-extend/)
67. **[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 · 75 citations*
68. **[Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA](https://md.research.elamur.ai/free/en/papers/wang-2024-leave-no-document-behind-benchmarking/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Minzheng Wang, Longze Chen, Fu Cheng, et al.*2024 · 71 citations*
69. **[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 · 71 citations*
70. **[MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/wang-2025-mac-sql-multi-agent-collaborative/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Bing Wang, Changyu Ren, Jian Yang, et al.*2025 · 67 citations*
71. **[xLAM: A Family of Large Action Models to Empower AI Agent Systems](https://md.research.elamur.ai/free/en/papers/zhang-2025-xlam-family-large-action-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jianguo Zhang, Tian Lan, Ming Zhu, et al.*2025 · 67 citations*
72. [**MagicPIG: LSH Sampling for Efficient LLM Generation arXiv:2410.16179**Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-magicpig-lsh-sampling-efficient-llm/)
73. [**GLM-4-Voice: Towards Intelligent and Human-Like End-to-End Spoken Chatbot arXiv:2412.02612**Aohan Zeng, Zhengxiao Du, Mingdao Liu, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-glm-4-voice-intelligent/)
74. **[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 · 61 citations*
75. [**OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models arXiv:2402.01739**Fuzhao Xue, Zian Zheng, Yao Fu, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/xue-2024-openmoe-early-effort-open-mixture/)
76. **[BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models](https://md.research.elamur.ai/free/en/papers/dong-2024-bamboo-comprehensive-benchmark-evaluating-long/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zican Dong, Tianyi Tang, Junyi Li, et al.*2024 · 59 citations*
77. [**Scaling Laws of RoPE-based Extrapolation arXiv:2310.05209**Xiaoran Liu, Hang Yan, Shuo Zhang, et al.*2023 · 53 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-scaling-laws-rope-based/)
78. [**Getting the most out of your tokenizer for pre-training and domain adaptation arXiv:2402.01035**Gautier Dagan, Gabriel Synnaeve, Baptiste Roziere*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dagan-2024-getting-most-out-tokenizer-pre/)
79. [**Observational Scaling Laws and the Predictability of Language Model Performance arXiv:2405.10938**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/)
80. [**Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling arXiv:2408.16737**Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.*2024 · 26 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2024-smaller-weaker-yet-better-training/)
81. [**Are Large Language Models Robust Coreference Resolvers? arXiv:2305.14489**Nghia T. Le, Alan Ritter*2023 · 26 citations*](https://md.research.elamur.ai/free/en/papers/le-2023-large-language-models-robust-coreference/)
82. **[Major Entity Identification: A Generalizable Alternative to Coreference Resolution](https://md.research.elamur.ai/free/en/papers/manikantan-2024-major-entity-identification-generalizable-alternative/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kawshik Manikantan, Shubham Toshniwal, Makarand Tapaswi, et al.*2024 · 13 citations*
83. **[from Benign import Toxic: Jailbreaking the Language Model via Adversarial Metaphors](https://md.research.elamur.ai/free/en/papers/yan-2025-benign-import-toxic-jailbreaking-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Yan, Sheng Sun, Zenghao Duan, et al.*2025 · 12 citations*
84. **[Scaling Laws for Code: A More Data-Hungry Regime](https://md.research.elamur.ai/free/en/papers/luo-2026-scaling-laws-code-more-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xianzhen Luo, Wenzhen Zheng, Qingfu Zhu, et al.*2026 · 3 citations*
85. [**Enhancing TTS Stability in Hebrew using Discrete Semantic Units**Ella Zeldes, Or Tal, Yossi Adi*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/zeldes-2024-enhancing-tts-stability-hebrew-using/)
86. **[Do Factual Recall Mechanisms Carry over from Text to Speech in Multimodal Language Models?](https://md.research.elamur.ai/free/en/papers/modica-2026-do-factual-recall-mechanisms-carry/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Luca Modica, Filip Landin, Mehrdad Farahani, et al.*2026*
87. **[Survey on Application of Retrieval-augmented Generation in Software Engineering (检索增强生成在软件工程中的应用综述)](https://md.research.elamur.ai/free/en/papers/zhang-2025-application-retrieval-augmented/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Quanjun Zhang (张犬俊), Yang Xie (谢杨), Chunrong Fang (房春荣), et al.*2025*
88. **[Survey on Code Generation with LLM-based Agents (基于大语言模型智能体的代码生成综述)](https://md.research.elamur.ai/free/en/papers/dong-2025-code-generation-llm/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yihong Dong (董益宏), Xue Jiang (姜雪), Jiaru Qian (钱家如), et al.*2025*

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