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20242026
most citedBeyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models

1 citations · 1 across the 14 of their papers we have counts for

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cs.AI2026

Dynamic Agent Skills: A Lifecycle Survey and Taxonomy of Evolving Skill Libraries

Yubo Li

Large language model agents increasingly store reusable procedures outside the model. These reusable procedures are often called \emph{skills}: they may be code functions, natural-…

cs.AI2026

SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks

Xiangyi Li, Yimin Liu, Wenbo Chen +75

Agent Skills are structured packages of procedural knowledge that augment large language model (LLM) agents at inference time. Despite rapid adoption, there is no standard way to m…

cs.AI2026

The Chain Holds, the Answer Folds: Trace-Answer Dissociation in Reasoning Models Under Adversarial Pressure

Yubo Li, Ramayya Krishnan, Rema Padman

Reasoning models are evaluated on single-turn benchmarks but deployed in multi-turn dialogue, where users push back on correct answers. Under sustained adversarial pressure we find…

cs.AI2026

PANDO: Efficient Multimodal AI Agents via Online Skill Distillation

Yubo Li, Yidi Miao, Yuntian Shen +1

Recent advances in multimodal web agents often rely on increased inference-time computation, including rollout search, verifier passes, offline skill discovery, and specialist mode…

cs.AI2026

Consistency of Large Reasoning Models Under Multi-Turn Attacks

Yubo Li, Ramayya Krishnan, Rema Padman

Large reasoning models with reasoning capabilities achieve state-of-the-art performance on complex tasks, but their robustness under multi-turn adversarial pressure remains underex…

cs.AI2025

Co-Alignment: Rethinking Alignment as Bidirectional Human-AI Cognitive Adaptation

Yubo Li, Weiyi Song

Current AI alignment through RLHF follows a single directional paradigm that AI conforms to human preferences while treating human cognition as fixed. We propose a shift to co-alig…