🧑‍🔬 Who cites Rishabh Tiwari

90 citations of their works from 90 papers of our library (of the 149,439 whose bibliographies we read) · 27 with a page here, the most cited first · ← Rishabh Tiwari

1. REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage NormalizationarXiv:2501.03262Jian Hu, Jason Klein Liu, Haotian Xu, et al.2025 · 104 citations
2. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
3. AI Scientists Fail Without Strong Implementation CapabilityarXiv:2506.01372Minjun Zhu, Qiujie Xie, Yixuan Weng, et al.2025 · 12 citations
4. UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated SupervisionAnnual Meeting of the Association for Computational Linguistics (ACL)Zhen Fang, Ruiyan Han, XinYu Sun, et al.2026 · 11 citations
5. Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent EvaluationarXiv:2510.11977Sayash Kapoor, Benedikt Stroebl, Peter Kirgis, et al.2025 · 11 citations
6. KL for a KL: On-Policy Distillation with Control Variate BaselinearXiv:2605.07865Minjae Oh, Sangjun Song, Gyubin Choi, et al.2026 · 8 citations
7. Mem²Evolve: Towards Self-Evolving Agents via Co-Evolutionary Capability Expansion and Experience DistillationAnnual Meeting of the Association for Computational Linguistics (ACL)Zihao Cheng, Zeming Liu, Yingyu Shan, et al.2026 · 5 citations
8. BILLY: Steering Large Language Models via Merging Persona Vectors for Creative GenerationConference of the European Chapter of the Association for Computational Linguistics (EACL)Tsung-Min Pai, Jui-I Wang, Li-Chun Lu, et al.2026 · 4 citations
9. Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box SystemsarXiv:2505.17968Jiayi Geng, Howard Chen, Dilip Arumugam, et al.2025 · 4 citations
10. J4R: Learning to Judge with Equivalent Initial State Group Relative Policy OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Austin Xu, Yilun Zhou, Xuan-Phi Nguyen, et al.2026 · 3 citations
11. Metacognitive Self-Correction for Multi-Agent System via Prototype-Guided Next-Execution ReconstructionFindings of the Association for Computational LinguisticsXu Shen, Qi Zhang, Song Wang, et al.2026 · 3 citations
12. ComfyUI-R1: Exploring Reasoning Models for Workflow GenerationFindings of the Association for Computational LinguisticsZhenran Xu, Yiyu Wang, Xue Yang, et al.2026 · 1 citation
13. Fine-Grained Detection of Context-Grounded Hallucinations Using LLMsFindings of the Association for Computational LinguisticsYehonatan Peisakhovsky, Zorik Gekhman, Yosi Mass, et al.2026 · 1 citation
14. From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language ModelsFindings of the Association for Computational LinguisticsJiaxin Zhang, Wendi Cui, Zhuohang Li, et al.2026 · 1 citation
15. RAFFLES: Reasoning-based Attribution of Faults for LLM SystemsConference of the European Chapter of the Association for Computational Linguistics (EACL)Chenyang Zhu, Spencer Hong, Jingyu Wu, et al.2026 · 1 citation
16. TAGS: A Test-Time Generalist–Specialist Framework with Retrieval-Augmented Reasoning and VerificationFindings of the Association for Computational LinguisticsJianghao Wu, Feilong Tang, Yulong Li, et al.2026 · 1 citation
17. Verification-Aware Planning for Multi-Agent SystemsConference of the European Chapter of the Association for Computational Linguistics (EACL)Tianyang Xu, Dan Zhang, Kushan Mitra, et al.2026 · 1 citation
18. Action Boundary Blindness: When LLM Agents Cannot Tell Where One Action Ends and Another BeginsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhangyi Wang, Bingnan Yu, Jiexiang Xu, et al.2026
19. Agentic CLEAR: Automating Multi-Level Evaluation of LLM AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Asaf Yehudai, Lilach Eden, Michal Shmueli-Scheuer2026
20. BayesFlow: A Probability Inference Framework for Meta-Agent Assisted Workflow GenerationFindings of the Association for Computational LinguisticsBo Yuan, Yun Zhou, Zhichao Xu, et al.2026
21. CIA: Inferring the Communication Topology from LLM-based Multi-Agent SystemsAnnual Meeting of the Association for Computational Linguistics (ACL)Yongxuan Wu, Xixun Lin, He Zhang, et al.2026
22. FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use EnvironmentsFindings of the Association for Computational LinguisticsAmir Saeidi, Venkatesh Mishra, Souradeep Mukhopadhyay, et al.2026
23. LUMINA: Long-horizon Understanding for Multi-turn Interactive AgentsFindings of the Association for Computational LinguisticsAmin Rakhsha, Thomas Hehn, Pietro Mazzaglia, et al.2026
24. Superficial Success vs. Internal Breakdown: An Empirical Study of Generalization in Adaptive Multi-Agent SystemsFindings of the Association for Computational LinguisticsNamyeong So, Seokgyu Jang, Taeuk Kim2026
25. Taming “Zombie” Agents: A Markov State-Aware Framework for Resilient Multi-Agent EvolutionAnnual Meeting of the Association for Computational Linguistics (ACL)Taolin Zhang, Pukun Zhao, Qizhou Chen, et al.2026
26. The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAGAnnual Meeting of the Association for Computational Linguistics (ACL)Shu Zhou, Jinman Leng, Yufei Song, et al.2026
27. Thesis Proposal: When Does an Agent Know It Is Lost? Confidence Trajectory Analysis for Tool-Using LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhenjiang Mao2026

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