collaborators

14 papers

cs.AI2026

When Correct Beliefs Collapse: Epistemic Resilience of LLMs under Clinical Pressure

Boyu Xiao, Xiuqi Tian, Xuwen Song +4

Despite strong medical benchmark accuracy, LLMs can exhibit severe multi-turn sycophancy in clinical dialogue, abandoning initial correct diagnosis under escalating pressure. We pr…

cs.AI2026

GSEM: Graph-based Self-Evolving Memory for Experience Augmented Clinical Reasoning

Xiao Han, Yuzheng Fan, Sendong Zhao +2

Clinical decision-making agents can benefit from reusing prior decision experience. However, many memory-augmented methods store experiences as independent records without explicit…

cs.CL2026

From Latent Signals to Reflection Behavior: Tracing Meta-Cognitive Activation Trajectory in R1-Style LLMs

Yanrui Du, Yibo Gao, Sendong Zhao +6

R1-style LLMs have attracted growing attention for their capacity for self-reflection, yet the internal mechanisms underlying such behavior remain unclear. To bridge this gap, we a…

cs.CL2026

S3-CoT: Self-Sampled Succinct Reasoning Enables Efficient Chain-of-Thought LLMs

Yanrui Du, Sendong Zhao, Yibo Gao +9

Large language models (LLMs) equipped with chain-of-thought (CoT) achieve strong performance and offer a window into LLM behavior. However, recent evidence suggests that improvemen…

cs.AI2026

Orchestrating Intelligence: Confidence-Aware Routing for Efficient Multi-Agent Collaboration across Multi-Scale Models

Jingbo Wang, Sendong Zhao, Jiatong Liu +4

While multi-agent systems (MAS) have demonstrated superior performance over single-agent approaches in complex reasoning tasks, they often suffer from significant computational ine…

cs.CL2026

ArcAligner: Adaptive Recursive Aligner for Compressed Context Embeddings in RAG

Jianbo Li, Yi Jiang, Sendong Zhao +3

Retrieval-Augmented Generation (RAG) helps LLMs stay accurate, but feeding long documents into a prompt makes the model slow and expensive. This has motivated context compression,…