---
title: "Who cites The Llama 3 Herd of — page 2 — 7,682 citing papers"
description: "7,682 papers of the Elamur Research library cite «The Llama 3 Herd of Models», found in their bibliographies · page 2 of 15 · 101–200; the…"
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---
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# Who cites «The Llama 3 Herd of Models»

7,682 papers of our library cite it (of the 149,439 whose bibliographies we read) · 1459 with a page here, the most cited first · page 2 of 15 · 101–200 · [← back to «The Llama 3 Herd of Models»](https://md.research.elamur.ai/free/en/papers/grattafiori-2024-llama-3-herd-models/)

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101. [**ZeroSearch: Incentivize the Search Capability of LLMs without Searching arXiv:2505.04588**Hao Sun, Zile Qiao, Jiayan Guo, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/sun-2025-zerosearch-incentivize-search-capability-llms/)
102. [**Hymba: A Hybrid-head Architecture for Small Language Models arXiv:2411.13676**Xin Dong, Yonggan Fu, Shizhe Diao, et al.*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-hymba-hybrid-head-architecture-small/)
103. **[LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Models](https://md.research.elamur.ai/free/en/papers/zhu-2026-llada-1-5-variance-reduced/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fengqi Zhu, Rongzhen Wang, Shen Nie, et al.*2026 · 49 citations*
104. [**RM-R1: Reward Modeling as Reasoning arXiv:2505.02387**Xiusi Chen, Gaotang Li, Ziqi Wang, et al.*2025 · 49 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-rm-r1-reward-modeling-reasoning/)
105. [**Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy arXiv:2507.01352**Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.*2025 · 48 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-skywork-reward-v2-scaling/)
106. [**Long Context Compression with Activation Beacon arXiv:2401.03462**Peitian Zhang, Zheng Liu, Shitao Xiao, et al.*2024 · 47 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-long-context-compression-activation-beacon/)
107. **[Disentangling Memory and Reasoning Ability in Large Language Models](https://md.research.elamur.ai/free/en/papers/jin-2025-disentangling-memory-reasoning-ability-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingyu Jin, Weidi Luo, Sitao Cheng, et al.*2025 · 45 citations*
108. [**EuroLLM-9B: Technical Report arXiv:2506.04079**Pedro Henrique Martins, Joao Alves, Patrick Fernandes, et al.*2025 · 45 citations*](https://md.research.elamur.ai/free/en/papers/martins-2025-eurollm-9b-technical-report/)
109. [**olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Models arXiv:2502.18443**Jake Poznanski, Aman Rangapur, Jon Borchardt, et al.*2025 · 44 citations*](https://md.research.elamur.ai/free/en/papers/poznanski-2025-olmocr-unlocking-trillions-tokens-pdfs/)
110. [**LLM Pruning and Distillation in Practice: The Minitron Approach arXiv:2408.11796**Sharath Turuvekere Sreenivas, Saurav Muralidharan, Raviraj Joshi, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/sreenivas-2024-llm-pruning-distillation-practice-minitron/)
111. [**NVLM: Open Frontier-Class Multimodal LLMs arXiv:2409.11402**Wenliang Dai, Nayeon Lee, Boxin Wang, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dai-2024-nvlm-open-frontier-class-multimodal/)
112. **[BIG5-CHAT: Shaping LLM Personalities Through Training on Human-Grounded Data](https://md.research.elamur.ai/free/en/papers/li-2025-big5-chat-shaping-llm-personalities/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenkai Li, Jiarui Liu, Andy Liu, et al.*2025 · 42 citations*
113. **[Improve Vision Language Model Chain-of-thought Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2025-improve-vision-language-model-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruohong Zhang, Bowen Zhang, Yanghao Li, et al.*2025 · 42 citations*
114. **[Improving Chain-of-Thought Reasoning via Quasi-Symbolic Abstractions](https://md.research.elamur.ai/free/en/papers/ranaldi-2025-improving-chain-thought-reasoning-quasi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leonardo Ranaldi, Marco Valentino, Andre Freitas*2025 · 42 citations*
115. **[SemEval-2026 Task 13: Detecting Machine-Generated Code with Multiple Programming Languages, Generators, and Application Scenarios](https://md.research.elamur.ai/free/en/papers/orel-2026-semeval-2026-task-13-detecting/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Daniil Orel, Dilshod Azizov, Indraneil Paul, et al.*2026 · 41 citations*
116. [**Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling arXiv:2502.06703**Runze Liu, Junqi Gao, Jian Zhao, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-1b-llm-surpass-405b-llm/)
117. [**DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models arXiv:2507.09955**Luolin Xiong, Haofen Wang, Xi Chen, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2025-deepseek-paradigm-shifts-technical/)
118. [**Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved Sampling arXiv:2410.11325**Wenda Xu, Rujun Han, Zifeng Wang, et al.*2024 · 41 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-speculative-knowledge-distillation-bridging-teacher/)
119. **[MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scale](https://md.research.elamur.ai/free/en/papers/guo-2025-mammoth-vl-eliciting-multimodal-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiawei Guo, Tianyu Zheng, Yizhi Li, et al.*2025 · 40 citations*
120. **[Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent System](https://md.research.elamur.ai/free/en/papers/su-2025-many-heads-are-better-than/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoyang Su, Renqi Chen, Shixiang Tang, et al.*2025 · 40 citations*
121. [**Observational Scaling Laws and the Predictability of Language Model Performance arXiv:2405.10938**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/)
122. [**NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model arXiv:2508.14444**NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/basant-2025-nvidia-nemotron-nano-2-accurate/)
123. [**Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models arXiv:2504.03624**NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.*2025 · 38 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-h-family-accurate-efficient/)
124. **[CheckEval: A reliable LLM-as-a-Judge framework for evaluating text generation using checklists](https://md.research.elamur.ai/free/en/papers/lee-2025-checkeval-reliable-llm-as-judge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yukyung Lee, JoongHoon Kim, Jaehee Kim, et al.*2025 · 37 citations*
125. **[Checklists Are Better Than Reward Models For Aligning Language Models](https://md.research.elamur.ai/free/en/papers/viswanathan-2025-checklists-better-than-reward-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Vijay Viswanathan, Yanchao Sun, Shuang Ma, et al.*2025 · 37 citations*
126. [**CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings arXiv:2501.01257**Shanghaoran Quan, Jiaxi Yang, Bowen Yu, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/quan-2025-codeelo-benchmarking-competition-level-code/)
127. **[APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay](https://md.research.elamur.ai/free/en/papers/prabhakar-2025-apigen-mt-agentic-pipeline-multi/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Akshara Prabhakar, Zuxin Liu, Ming Zhu, et al.*2025 · 36 citations*
128. **[Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?](https://md.research.elamur.ai/free/en/papers/jin-2025-exploring-concept-depth-how-large/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Mingyu Jin, Qinkai Yu, Jingyuan Huang, et al.*2025 · 36 citations*
129. [**SciKnowEval: Evaluating Multi-level Scientific Knowledge of Large Language Models arXiv:2406.09098**Kehua Feng, Xinyi Shen, Weijie Wang, et al.*2024 · 36 citations*](https://md.research.elamur.ai/free/en/papers/feng-2024-sciknoweval-evaluating-multi-level-scientific/)
130. **[Direct Judgement Preference Optimization](https://md.research.elamur.ai/free/en/papers/wang-2025-direct-judgement-preference-optimization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**PeiFeng Wang, Austin Xu, Yilun Zhou, et al.*2025 · 35 citations*
131. **[MasRouter: Learning to Route LLMs for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/yue-2025-masrouter-learning-route-llms-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanwei Yue, Guibin Zhang, Boyang Liu, et al.*2025 · 35 citations*
132. [**On the Diversity of Synthetic Data and its Impact on Training Large Language Models arXiv:2410.15226**Hao Chen, Abdul Waheed, Xiang Li, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-diversity-synthetic-data-impact-training/)
133. [**EuroBERT: Scaling Multilingual Encoders for European Languages arXiv:2503.05500**Nicolas Boizard, Hippolyte Gisserot-Boukhlef, Duarte M. Alves, et al.*2025 · 34 citations*](https://md.research.elamur.ai/free/en/papers/boizard-2025-eurobert-scaling-multilingual-encoders-european/)
134. [**Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models arXiv:2411.07140**Yancheng He, Shilong Li, Jiaheng Liu, et al.*2024 · 34 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-chinese-simpleqa-chinese-factuality/)
135. [**OpenCodeReasoning: Advancing Data Distillation for Competitive Coding arXiv:2504.01943**Wasi Uddin Ahmad, Sean Narenthiran, Somshubra Majumdar, et al.*2025 · 33 citations*](https://md.research.elamur.ai/free/en/papers/ahmad-2025-opencodereasoning-advancing-data-distillation-competitive/)
136. [**Qwen3Guard Technical Report arXiv:2510.14276**Haiquan Zhao, Chenhan Yuan, Fei Huang, et al.*2025 · 33 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2025-qwen3guard-technical-report/)
137. **[Unveiling Privacy Risks in LLM Agent Memory](https://md.research.elamur.ai/free/en/papers/wang-2025-unveiling-privacy-risks-llm-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bo Wang, Weiyi He, Shenglai Zeng, et al.*2025 · 33 citations*
138. [**SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety arXiv:2404.05399**Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-safetyprompts-systematic-review-open-datasets/)
139. **[500xCompressor: Generalized Prompt Compression for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2025-500xcompressor-generalized-prompt-compression-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zongqian Li, Yixuan Su, Nigel Collier*2025 · 32 citations*
140. **[Benchmarking Linguistic Diversity of Large Language Models](https://md.research.elamur.ai/free/en/papers/guo-2025-benchmarking-linguistic-diversity-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yanzhu Guo, Guokan Shang, Chloé Clavel*2025 · 32 citations*
141. **[Evaluating Language Models as Synthetic Data Generators](https://md.research.elamur.ai/free/en/papers/kim-2025-evaluating-language-models-as-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Seungone Kim, Juyoung Suk, Xiang Yue, et al.*2025 · 32 citations*
142. **[TurboRAG: Accelerating Retrieval-Augmented Generation with Precomputed KV Caches for Chunked Text](https://md.research.elamur.ai/free/en/papers/lu-2025-turborag-accelerating-retrieval-augmented-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Songshuo Lu, Hua Wang, Yutian Rong, et al.*2025 · 32 citations*
143. **[VLSBench: Unveiling Visual Leakage in Multimodal Safety](https://md.research.elamur.ai/free/en/papers/hu-2025-vlsbench-unveiling-visual-leakage-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuhao Hu, Dongrui Liu, Hao Li, et al.*2025 · 32 citations*
144. **[Detection and Measurement of Syntactic Templates in Generated Text](https://md.research.elamur.ai/free/en/papers/shaib-2024-detection-measurement-syntactic-templates-generated/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chantal Shaib, Yanai Elazar, Junyi Jessy Li, et al.*2024 · 32 citations*
145. **[SelfCodeAlign: Self-Alignment for Code Generation](https://md.research.elamur.ai/free/en/papers/wei-2024-selfcodealign-self-alignment-code-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxiang Wei, Federico Cassano, Jiawei Liu, et al.*2024 · 32 citations*
146. [**Step-Audio 2 Technical Report arXiv:2507.16632**Boyong Wu, Chao Yan, Chen Hu, et al.*2025 · 31 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-step-audio-2-technical/)
147. **[Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations](https://md.research.elamur.ai/free/en/papers/hagele-2024-scaling-laws-compute-optimal-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alexander Hägele, Elie Bakouch, Atli Kosson, et al.*2024 · 31 citations*
148. **[Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?](https://md.research.elamur.ai/free/en/papers/he-2025-can-large-language-models-detect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yancheng He, Shilong Li, Jiaheng Liu, et al.*2025 · 30 citations*
149. **[CRMArena: Understanding the Capacity of LLM Agents to Perform Professional CRM Tasks in Realistic Environments](https://md.research.elamur.ai/free/en/papers/huang-2025-crmarena-understanding-capacity-llm-agents/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kung-Hsiang Huang, Akshara Prabhakar, Sidharth Dhawan, et al.*2025 · 30 citations*
150. **[G-Safeguard: A Topology-Guided Security Lens and Treatment on LLM-based Multi-agent Systems](https://md.research.elamur.ai/free/en/papers/wang-2025-g-safeguard-topology-guided-security/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shilong Wang, Guibin Zhang, Miao Yu, et al.*2025 · 30 citations*
151. **[PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides](https://md.research.elamur.ai/free/en/papers/zheng-2025-pptagent-generating-evaluating-presentations-beyond/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Zheng, Xinyan Guan, Hao Kong, et al.*2025 · 30 citations*
152. **[The Hidden Risks of Large Reasoning Models: A Safety Assessment of R1](https://md.research.elamur.ai/free/en/papers/zhou-2025-hidden-risks-large-reasoning-models/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Kaiwen Zhou, Chengzhi Liu, Xuandong Zhao, et al.*2025 · 30 citations*
153. [**Jamba-1.5: Hybrid Transformer-Mamba Models at Scale arXiv:2408.12570**Jamba Team: Barak Lenz, Alan Arazi, Amir Bergman, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/lenz-2024-jamba-1-5-hybrid-transformer/)
154. [**RMB: Comprehensively Benchmarking Reward Models in LLM Alignment arXiv:2410.09893**Enyu Zhou, Guodong Zheng, Binghai Wang, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-rmb-comprehensively-benchmarking-reward-models/)
155. [**Qwen3.5-Omni Technical Report arXiv:2604.15804**Qwen Team*2026 · 29 citations*](https://md.research.elamur.ai/free/en/papers/qwen-team-2026-qwen3-5-omni-technical/)
156. [**Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming arXiv:2501.18837**Mrinank Sharma, Meg Tong, Jesse Mu, et al.*2025 · 29 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2025-constitutional-classifiers-defending-against-universal/)
157. [**InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models arXiv:2503.06692**Yuchen Yan, Yongliang Shen, Yang Liu, et al.*2025 · 29 citations*](https://md.research.elamur.ai/free/en/papers/yan-2025-inftythink-breaking-length-limits-long/)
158. **[INVESTORBENCH: A Benchmark for Financial Decision-Making Tasks with LLM-based Agent](https://md.research.elamur.ai/free/en/papers/li-2025-investorbench-benchmark-financial-decision-making/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haohang Li, Yupeng Cao, Yangyang Yu, et al.*2025 · 29 citations*
159. **[SEA-LION: Southeast Asian Languages in One Network](https://md.research.elamur.ai/free/en/papers/ng-2025-sea-lion-southeast-asian-languages/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Raymond Ng, Thanh Ngan Nguyen, Huang Yuli, et al.*2025 · 29 citations*
160. [**Baichuan-Omni-1.5 Technical Report arXiv:2501.15368**Yadong Li, Jun Liu, Tao Zhang, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-omni-1-5/)
161. **[Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions](https://md.research.elamur.ai/free/en/papers/suh-2025-language-model-fine-tuning-scaled/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joseph Suh, Erfan Jahanparast, Suhong Moon, et al.*2025 · 28 citations*
162. **[Automatic Instruction Evolving for Large Language Models](https://md.research.elamur.ai/free/en/papers/zeng-2024-automatic-instruction-evolving-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weihao Zeng, Can Xu, Yingxiu Zhao, et al.*2024 · 28 citations*
163. **[Stable-RAG: Mitigating Retrieval-Permutation-Induced Hallucinations in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhang-2026-stable-rag-mitigating-retrieval-permutation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qianchi Zhang, Hainan Zhang, Liang Pang, et al.*2026 · 27 citations*
164. **[Are LLMs Better than Reported? Detecting Label Errors and Mitigating Their Effect on Model Performance](https://md.research.elamur.ai/free/en/papers/nahum-2025-are-llms-better-than-reported/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Omer Nahum, Nitay Calderon, Orgad Keller, et al.*2025 · 27 citations*
165. **[LLM Agents Making Agent Tools](https://md.research.elamur.ai/free/en/papers/wolflein-2025-llm-agents-making-agent-tools/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Georg Wölflein, Dyke Ferber, Daniel Truhn, et al.*2025 · 27 citations*
166. **[SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature](https://md.research.elamur.ai/free/en/papers/wadden-2025-sciriff-resource-enhance-language-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**David Wadden, Kejian Shi, Jacob Morrison, et al.*2025 · 27 citations*
167. **[Separating Tongue from Thought: Activation Patching Reveals Language-Agnostic Concept Representations in Transformers](https://md.research.elamur.ai/free/en/papers/dumas-2025-separating-tongue-thought-activation-patching/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Clément Dumas, Chris Wendler, Veniamin Veselovsky, et al.*2025 · 27 citations*
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169. [**Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling arXiv:2408.16737**Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2024-smaller-weaker-yet-better-training/)
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