5 citations · 11 across the 27 of their papers we have counts for
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cs.AI2026
AJ-Bench: Benchmarking Agent-as-a-Judge for Environment-Aware Evaluation
Wentao Shi, Yu Wang, Yuyang Zhao +8
As reinforcement learning continues to scale the training of large language model-based agents, reliably verifying agent behaviors in complex environments has become increasingly c…
cs.AI2026
ReactBench: A Benchmark for Topological Reasoning in MLLMs on Chemical Reaction Diagrams
Qiang Xu, Shengyuan Bai, Yu Wang +6
Multimodal Large Language Models (MLLMs) excel at recognizing individual visual elements and reasoning over simple linear diagrams. However, when faced with complex topological str…
cs.AI2026★ 1 cited
A Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agents
Tianxin Wei, Ting-Wei Li, Zhining Liu +26
Reasoning is a fundamental cognitive process underlying inference, problem-solving, and decision-making. While large language models (LLMs) demonstrate strong reasoning capabilitie…