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20242026
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cs.CL2026

Beyond Semantics: An Evidential Reasoning-Aware Multi-View Learning Framework for Trustworthy Mental Health Prediction

Yucheng Ruan, Ling Huang, Qika Lin +2

Automated mental health prediction using textual data has shown promising results with deep learning and large language models. However, deploying these models in high-stakes real-…

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.CL2025

GEM: Empowering MLLM for Grounded ECG Understanding with Time Series and Images

Xiang Lan, Feng Wu, Kai He +3

While recent multimodal large language models (MLLMs) have advanced automated ECG interpretation, they still face two key limitations: (1) insufficient multimodal synergy between t…

cs.CL2025

Anchoring Refusal Direction: Mitigating Safety Risks in Tuning via Projection Constraint

Yanrui Du, Fenglei Fan, Sendong Zhao +6

Instruction Fine-Tuning (IFT) has been widely adopted as an effective post-training strategy to enhance various abilities of Large Language Models (LLMs). However, prior studies ha…

cs.CL2025

DivScore: Zero-Shot Detection of LLM-Generated Text in Specialized Domains

Zhihui Chen, Kai He, Yucheng Huang +2

Detecting LLM-generated text in specialized and high-stakes domains like medicine and law is crucial for combating misinformation and ensuring authenticity. However, current zero-s…