PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving (2025 · 16 citations)
LLM-based agents and test-time search methods often fail on "natural planning" tasks, such as scheduling meetings or planning trips described in plain language.
Benchmarking Open-ended Audio Dialogue Understanding for Large Audio-Language Models (2025 · 12 citations)
Large Audio-Language Models (LALMs) such as GPT-4o can now hold spoken conversations directly with users. Until this work, however, no benchmark tested how well they understand open-ended audio dialogue. Earlier evaluations covered basic audio tasks, audio QA driven by text instructions, or general-purpose chat only.

All works

4 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models ↗arXiv:2311.17600 · no summary yetXin Liu et al.2023 · 152 citations
PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem SolvingConference on Empirical Methods in Natural Language Processing (EMNLP)Mihir Parmar, Xin Liu, Palash Goyal, et al.2025 · 16 citations
Benchmarking Open-ended Audio Dialogue Understanding for Large Audio-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Kuofeng Gao, Shu-Tao Xia, Ke Xu, et al.2025 · 12 citations
You Only Need One Single Token to Refine Safety Alignment ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetWenqian Yu et al.2026

Co-authors here

12 of 14 co-authors with a page, the most papers together first.

Where their works here were published, the most works first, with the editions of those that have a page.

Papers of our library cite their works 107 times (of the 149,439 papers whose bibliographies we read); 19 citing papers with a page here →.

Updated 1 November 2026