---
title: "Who cites Hengyi Cai — 266 papers of our library"
description: "266 papers of the Elamur Research library cite the works of Hengyi Cai, found in their bibliographies; the most cited first."
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---
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# Who cites Hengyi Cai

267 citations of their works from 266 papers of our library (of the 149,439 whose bibliographies we read) · 70 with a page here, the most cited first · [← Hengyi Cai](https://md.research.elamur.ai/free/en/authors/hengyi-cai/)

1. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
2. [**A Survey of Data Augmentation Approaches for NLP arXiv:2105.03075**Steven Y. Feng, Varun Gangal, Jason Wei, et al.*2021 · 940 citations*](https://md.research.elamur.ai/free/en/papers/feng-2021-survey-data-augmentation-approaches-nlp/)
3. [**Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters arXiv:2408.03314**Charlie Snell, Jaehoon Lee, Kelvin Xu, et al.*2024 · 567 citations*](https://md.research.elamur.ai/free/en/papers/snell-2024-scaling-llm-test-time-compute/)
4. [**Tulu 3: Pushing Frontiers in Open Language Model Post-Training arXiv:2411.15124**Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.*2024 · 423 citations*](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/)
5. **[Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives](https://md.research.elamur.ai/free/en/papers/gao-2023-large-language-models-empowered-agent/) [Humanities and Social Sciences Communications](https://md.research.elamur.ai/free/en/venues/humanities-and-social-sciences-communications/)**Chen Gao, Xiaochong Lan, Nian Li, et al.*2023 · 344 citations*
6. [**Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning arXiv:2503.09516**Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.*2025 · 322 citations*](https://md.research.elamur.ai/free/en/papers/jin-2025-search-r1-training-llms-reason/)
7. **[An Analysis of Simple Data Augmentation for Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/dai-2020-analysis-simple-data-augmentation-named/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Xiang Dai, Heike Adel*2020 · 266 citations*
8. **[An Empirical Survey of Data Augmentation for Limited Data Learning in NLP](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 254 citations*
9. **[Tool Learning with Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/qu-2024-tool-learning-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Changle Qu, Sunhao Dai, Xiaochi Wei, et al.*2024 · 195 citations*
10. **[Knowledge Conflicts for LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 182 citations*
11. [**Physics of Language Models: Part 3.1, Knowledge Storage and Extraction arXiv:2309.14316**Zeyuan Allen-Zhu, Yuanzhi Li*2023 · 116 citations*](https://md.research.elamur.ai/free/en/papers/allen-zhu-2023-physics-language-models-part-3/)
12. [**ToolACE: Winning the Points of LLM Function Calling arXiv:2409.00920**Weiwen Liu; Xu Huang; Xingshan Zeng; Xinlong Hao; Shuai Yu; Dexun Li; Shuai Wang; Weinan Gan; Zhengying Liu; Yuanqing Yu; Zezhong Wang; Yuxian Wang; Wu Ning; Yutai Hou; Bin Wang; Chuhan Wu; Xinzhi Wang; Yong Liu; Yasheng Wang; Duyu Tang; Dandan Tu; Lifeng Shang; Xin Jiang; Ruiming Tang; Defu Lian; Qun Liu;, Enhong Chen*2024 · 101 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-toolace-winning-points-llm-function/)
13. [**Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security arXiv:2401.05459**Yuanchun Li, Hao Wen, Weijun Wang, et al.*2024 · 100 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-personal-llm-agents-insights-survey/)
14. [**Automated Design of Agentic Systems arXiv:2408.08435**Shengran Hu, Cong Lu, Jeff Clune*2024 · 89 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-automated-design-agentic-systems/)
15. [**Retrieval-Augmented Generation with Graphs (GraphRAG) arXiv:2501.00309**Haoyu Han, Yu Wang, Harry Shomer, et al.*2025 · 87 citations*](https://md.research.elamur.ai/free/en/papers/han-2025-retrieval-augmented-generation-graphs-graphrag/)
16. [**Rethinking Interpretability in the Era of Large Language Models arXiv:2402.01761**Chandan Singh, Jeevana Priya Inala, Michel Galley, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-rethinking-interpretability-era-large-language/)
17. [**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/)
18. **[TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space](https://md.research.elamur.ai/free/en/papers/zhang-2024-truthx-alleviating-hallucinations-editing-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaolei Zhang, Tian Yu, Yang Feng*2024 · 57 citations*
19. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/)
20. **[StepSearch: Igniting LLMs Search Ability via Step-Wise Proximal Policy Optimization](https://md.research.elamur.ai/free/en/papers/zheng-2025-stepsearch-igniting-llms-search-ability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xuhui Zheng, Kang An, Ziliang Wang, et al.*2025 · 19 citations*
21. **[Adaptive Tool Use in Large Language Models with Meta-Cognition Trigger](https://md.research.elamur.ai/free/en/papers/li-2025-adaptive-tool-use-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenjun Li, Dexun Li, Kuicai Dong, et al.*2025 · 16 citations*
22. **[ToolHop: A Query-Driven Benchmark for Evaluating Large Language Models in Multi-Hop Tool Use](https://md.research.elamur.ai/free/en/papers/ye-2025-toolhop-query-driven-benchmark-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junjie Ye, Zhengyin Du, Xuesong Yao, et al.*2025 · 15 citations*
23. **[What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective](https://md.research.elamur.ai/free/en/papers/li-2025-what-happened-llms-layers-when/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ming Li, Yanhong Li, Tianyi Zhou*2025 · 15 citations*
24. **[EXCGEC: A Benchmark for Edit-Wise Explainable Chinese Grammatical Error Correction](https://md.research.elamur.ai/free/en/papers/ye-2024-excgec-benchmark-edit-wise-explainable/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Jingheng Ye, Shang Qin, Yinghui Li, et al.*2024 · 15 citations*
25. **[Explainability and Interpretability of Multilingual Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/resck-2025-explainability-interpretability-multilingual-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lucas Resck, Isabelle Augenstein, Anna Korhonen*2025 · 11 citations*
26. **[When2Call: When (not) to Call Tools](https://md.research.elamur.ai/free/en/papers/ross-2025-when2call-when-not-call-tools/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hayley Ross, Ameya Sunil Mahabaleshwarkar, Yoshi Suhara*2025 · 11 citations*
27. **[A Survey of Inductive Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2026-survey-inductive-reasoning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kedi Chen, Dezhao Ruan, Yuhao Dan, et al.*2026 · 10 citations*
28. **[Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-unconditional-truthfulness-learning-unconditional-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, et al.*2025 · 10 citations*
29. **[FaithLM: Towards Faithful Explanations for Large Language Models](https://md.research.elamur.ai/free/en/papers/chuang-2026-faithlm-faithful-explanations-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, et al.*2026 · 9 citations*
30. **[Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-locate-steer-improve-practical-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hengyuan Zhang, Zhihao Zhang, Ercong Nie, et al.*2026 · 9 citations*
31. **[Android Coach: Improve Online Agentic Training Efficiency with Single State Multiple Actions](https://md.research.elamur.ai/free/en/papers/gan-2026-android-coach-improve-online-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guo Gan, Yuxuan Ding, Cong Chen, et al.*2026 · 7 citations*
32. **[NesTools: A Dataset for Evaluating Nested Tool Learning Abilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/han-2025-nestools-dataset-evaluating-nested-tool/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Han Han, Tong Zhu, Xiang Zhang, et al.*2025 · 7 citations*
33. **[EVOTOOL: Self-Evolving Tool-Use Policy Optimization in LLM Agents via Blame-Aware Mutation and Diversity-Aware Selection](https://md.research.elamur.ai/free/en/papers/yang-2026-evotool-self-evolving-tool-use/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuo Yang, Caren Han, Xueqi Ma, et al.*2026 · 6 citations*
34. **[Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments](https://md.research.elamur.ai/free/en/papers/ye-2026-feedback-driven-tool-use-improvements/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junjie Ye, Changhao Jiang, Zhengyin Du, et al.*2026 · 6 citations*
35. **[LoopTool: Closing the Data–Training Loop for Robust LLM Tool Calls](https://md.research.elamur.ai/free/en/papers/zhang-2026-looptool-closing-data-training-loop/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kangning Zhang, Weiwen Liu, Wenxiang Jiao, et al.*2026 · 6 citations*
36. **[MAVEN-FACT: A Large-scale Event Factuality Detection Dataset](https://md.research.elamur.ai/free/en/papers/li-2024-maven-fact-large-scale-event/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chunyang Li, Hao Peng, Xiaozhi Wang, et al.*2024 · 6 citations*
37. **[EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis](https://md.research.elamur.ai/free/en/papers/song-2026-envscaler-scaling-tool-interactive-environments/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaoshuai Song, Haofei Chang, Guanting Dong, et al.*2026 · 5 citations*
38. **[ToolScope: Enhancing LLM Agent Tool Use through Tool Merging and Context-Aware Filtering](https://md.research.elamur.ai/free/en/papers/liu-2026-toolscope-enhancing-llm-agent-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Marianne Menglin Liu, Daniel Garcia, Fjona Parllaku, et al.*2026 · 4 citations*
39. **[Controlling Reading Ease with Gaze-Guided Text Generation](https://md.research.elamur.ai/free/en/papers/sauberli-2026-controlling-reading-ease-gaze-guided/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Andreas Säuberli, Darja Jepifanova, Diego Frassinelli, et al.*2026 · 3 citations*
40. **[Argument-Based Consistency in Toxicity Explanations of LLMs](https://md.research.elamur.ai/free/en/papers/mothilal-2026-argument-based-consistency-toxicity-explanations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ramaravind Kommiya Mothilal, Joanna Roy, Syed Ishtiaque Ahmed, et al.*2026 · 2 citations*
41. **[Do LLMs Encode Functional Importance of Reasoning Tokens ?](https://md.research.elamur.ai/free/en/papers/singh-2026-do-llms-encode-functional-importance/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Janvijay Singh, Dilek Hakkani-Tür*2026 · 2 citations*
42. **[Failure makes the agent stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions](https://md.research.elamur.ai/free/en/papers/su-2026-failure-makes-agent-stronger-enhancing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junhao Su, Yuanliang Wan, Junwei Yang, et al.*2026 · 2 citations*
43. **[MatchTIR: Fine-Grained Supervision for Tool-Integrated Reasoning via Bipartite Matching](https://md.research.elamur.ai/free/en/papers/qu-2026-matchtir-fine-grained-supervision-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Changle Qu, Sunhao Dai, Hengyi Cai, et al.*2026 · 1 citation*
44. **[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*
45. **[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*
46. **[The Thin Line Between Comprehension and Persuasion in LLMs](https://md.research.elamur.ai/free/en/papers/wynter-2026-thin-line-between-comprehension-persuasion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adrian de Wynter, Tangming Yuan*2026 · 1 citation*
47. **[ToolDreamer: Instilling LLM Reasoning Into Tool Retrievers](https://md.research.elamur.ai/free/en/papers/sengupta-2026-tooldreamer-instilling-llm-reasoning-into/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Saptarshi Sengupta, Zhengyu Zhou, Jun Araki, et al.*2026 · 1 citation*
48. **[Actionable Interpretability for Churn Classification: A Text Bottleneck Model Case Study at a Major Telecom Provider](https://md.research.elamur.ai/free/en/papers/sauter-2026-actionable-interpretability-churn-classification-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Adrian Sauter, Vera Neplenbroek, Georgios Vlassopoulos, et al.*2026*
49. **[AdaptiveK: Complexity-Driven Sparse Autoencoders for Interpretable Language Model Representations](https://md.research.elamur.ai/free/en/papers/yao-2026-adaptivek-complexity-driven-sparse-autoencoders/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifei Yao, Hanrong Zhang, Mengnan Du*2026*
50. **[Assertion-Conditioned Compliance: A Provenance-Aware Vulnerability in Multi-Turn Tool-Calling Agents](https://md.research.elamur.ai/free/en/papers/waqas-2026-assertion-conditioned-compliance-provenance-aware/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Daud Waqas, Aaryamaan Golthi, Erika Hayashida, et al.*2026*
51. **[Beyond Static Toolsets: Self-Evolving LLM Tool Agents via Continual Documentation Adaptation](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-static-toolsets-self-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bin Wu, Edgar Meij, Emine Yilmaz*2026*
52. [**Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives arXiv:2607.18443**Polina Tsvilodub, Fausto Carcassi, Michael Franke*2026*](https://md.research.elamur.ai/free/en/papers/tsvilodub-2026-computational-models-pragmatic-reasoning-flexible/)
53. **[DART: Mitigating Harm Drift in Difference-Aware LLMs via Distill-Audit-Repair Training](https://md.research.elamur.ai/free/en/papers/pan-2026-dart-mitigating-harm-drift-difference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ziwen Pan, Zihan Liang, Jad Kabbara, et al.*2026*
54. [**English is Not All You Need: Systematically Exploring the Role of Multilinguality in LLM Post-Training arXiv:2604.13286**Mehak Dhaliwal, Shashwat Chaurasia, Yao Qin, et al.*2026*](https://md.research.elamur.ai/free/en/papers/dhaliwal-2026-english-all-need-systematically-exploring/)
55. **[EvoMemKG: An Evolvable Memory Agent for Multi-hop Knowledge Graph Reasoning](https://md.research.elamur.ai/free/en/papers/tian-2026-evomemkg-evolvable-memory-agent-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shiyu Tian, Shuyue Xing, Zhuoxin Han, et al.*2026*
56. **[FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments](https://md.research.elamur.ai/free/en/papers/saeidi-2026-fama-failure-aware-meta-agentic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Amir Saeidi, Venkatesh Mishra, Souradeep Mukhopadhyay, et al.*2026*
57. **[From Heads to Neurons: Causal Attribution and Steering in Multi-Task Vision–Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-heads-neurons-causal-attribution-steering/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qidong Wang, Junjie Hu, Ming Jiang*2026*
58. **[GenesisFunc: Multi-Agent Data Generation for Accurate and Generalizable Function-Calling](https://md.research.elamur.ai/free/en/papers/xu-2026-genesisfunc-multi-agent-data-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao-Xiang Xu, Chong Deng, Jiaqing Liu, et al.*2026*
59. **[Harnessing the Latent Space: From Steering Vectors to Model Calibrators for Control and Trust](https://md.research.elamur.ai/free/en/papers/subramani-2026-harnessing-latent-space-steering-vectors/) [Big Picture v2: Crafting a Research Narrative](https://md.research.elamur.ai/free/en/venues/bigpicture/)**Nishant Subramani*2026*
60. **[LIBERTy: A Causal Framework for Benchmarking Concept-Based Explanations of LLMs with Structural Counterfactuals](https://md.research.elamur.ai/free/en/papers/toker-2026-liberty-causal-framework-benchmarking-concept/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gilat Toker, Nitay Calderon, Ohad Amosy, et al.*2026*
61. **[Mapping the Circumplex of Affect: Geometric Analysis of Emotion Representations via Hyperspherical Contrastive Learning](https://md.research.elamur.ai/free/en/papers/yamauchi-2026-mapping-circumplex-affect-geometric-analysis/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yusuke Yamauchi, Akiko Aizawa*2026*
62. **[mllm-shap: A Shapley Value Explainability Platform for Text-Audio Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/muszynski-2026-mllm-shap-shapley-value-explainability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jakub Muszyński, Paweł Pozorski, Maria Ganzha*2026*
63. **[Parallel Universes, Parallel Languages: A Comprehensive Study on LLM-based Multilingual Counterfactual Example Generation](https://md.research.elamur.ai/free/en/papers/wang-2026-parallel-universes-parallel-languages-comprehensive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qianli Wang, Van Bach Nguyen, Yihong Liu, et al.*2026*
64. **[SGA-MCTS: Decoupling Planning from Execution via Training-Free Atomic Experience Retrieval](https://md.research.elamur.ai/free/en/papers/xie-2026-sga-mcts-decoupling-planning-execution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xin Xie, Dongyun Xue, Wuguannan Yao, et al.*2026*
65. **[Training Verifier to Assessing Complex Real-World Tool-Use Trajectories](https://md.research.elamur.ai/free/en/papers/sun-2026-training-verifier-assessing-complex-real/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Linzhuang Sun, Mingyang Chen, Hao Liang, et al.*2026*
66. **[TriEx: A Game-based Tri-View Framework for Explaining Internal Reasoning in Multi-Agent LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-triex-game-based-tri-view/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyi Wang, Chen Zhang, Wenjun Peng, et al.*2026*
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