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From the 1 of 18 linked papers with an AI index.

most citedBenchmarking Retrieval-Augmented Generation for Chemistry

1 citations · 1 across the 10 of their papers we have counts for

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cs.AI2026

How Hard Does It Think? Analyzing Step-Aware Reasoning Energy in LLM Chain-of-Thought Trajectories

Hui Wei, Junda Wu, Sheldon Yu +8

Understanding how computational effort is allocated across individual chain-of-thought (CoT) reasoning steps remains an open challenge: existing interpretability methods rely on ou…

cs.AI2026

Retrieval is Cheap, Show Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation

Jiashuo Sun, Jimeng Shi, Yixuan Xie +10

Retrieval-Augmented Generation (RAG) has become a standard approach for knowledge-intensive question answering, but existing systems remain brittle on multi-hop questions, where so…

cs.AI2026

OLIVIA: Online Learning via Inference-time Action Adaptation for Decision Making in LLM ReAct Agents

Sheldon Yu, Junda Wu, Xintong Li +6

Large language model agents interleave reasoning, action selection, and observation to solve sequential decision-making tasks. In deployed settings where agents repeatedly handle r…

cs.AI2026

SkillOS: Learning Skill Curation for Self-Evolving Agents

Siru Ouyang, Jun Yan, Yanfei Chen +13

LLM-based agents are increasingly deployed to handle streaming tasks, yet they often remain one-off problem solvers that fail to learn from past interactions. Reusable skills disti…

cs.AI2026

ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory

Siru Ouyang, Jun Yan, I-Hung Hsu +14

With the growing adoption of large language model agents in persistent real-world roles, they naturally encounter continuous streams of tasks. A key limitation, however, is their f…