activity
20232026
most citedChain of Agents: Large Language Models Collaborating on Long-Context Tasks

9 citations · 20 across the 17 of their papers we have counts for

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5 papers · 1 filter

cs.CL2026

ToolSciVer: Multimodal Scientific Claim Verification with Visual Tool Augmented Reinforcement Learning

Binglin Zhou, Peng Shi, Ryo Kamoi +2

Multimodal Scientific Claim Verification (MSCV) requires models to verify scientific claims using visually grounded evidence from papers, including figures, tables, charts, and tex…

cs.CL2026

SIMMER: Benchmarking Latent Failures in LLM Executable Planning with a World Model

Xiaoxin Lu, Ranran Haoran Zhang, Rui Zhang

Large language models (LLMs) are increasingly deployed as planners for autonomous agents in household environments. While existing benchmarks evaluate whether LLM-generated plans e…

cs.CL2026

From Correctness to Preference: A Framework for Personalized Agentic Reinforcement Learning

Ranxu zhang, zeyang li, Jiacheng Huang +5

Agentic reinforcement learning (Agentic RL) has achieved strong progress in tasks with clear success signals. However, many real-world agent applications require user-conditioned b…

cs.AI2026

Nexus : An Agentic Framework for Context-Aware Time Series Forecasting

Sarkar Snigdha Sarathi Das, Palash Goyal, Mihir Parmar +6

Language models have emerged as highly capable reasoners, yet their performance in time series forecasting remains uneven across domains and levels of contextual grounding. This is…

cs.CL2026

Evaluating LLM-Simulated Conversations in Modeling Inconsistent and Uncollaborative Behaviors in Human Social Interaction

Ryo Kamoi, Ameya Godbole, Binglin Zhou +5

Simulating human conversations using large language models (LLMs) has emerged as a scalable methodology for modeling human social interaction. This paper reconsiders the evaluation…