4 papers
Think Deep, Not Just Long: Measuring LLM Reasoning Effort via Deep-Thinking Tokens
Wei-Lin Chen, Liqian Peng, Tian Tan +5
Large language models (LLMs) have demonstrated impressive reasoning capabilities by scaling test-time compute via long Chain-of-Thought (CoT). However, recent findings suggest that…
Learning to Solve and Verify: A Self-Play Framework for Code and Test Generation
Zi Lin, Sheng Shen, Ilia Kulikov +3
Recent advances in large language models (LLMs) have improved their performance on coding benchmarks. However, improvement is plateauing due to the exhaustion of readily available…
Analysis of LLM Bias (Chinese Propaganda & Anti-US Sentiment) in DeepSeek-R1 vs. ChatGPT o3-mini-high
PeiHsuan Huang, ZihWei Lin, Simon Imbot +2
Large language models (LLMs) increasingly shape public understanding and civic decisions, yet their ideological neutrality is a growing concern. While existing research has explore…
Amplified Vulnerabilities: Structured Jailbreak Attacks on LLM-based Multi-Agent Debate
Senmao Qi, Yifei Zou, Peng Li +3
Multi-Agent Debate (MAD), leveraging collaborative interactions among Large Language Models (LLMs), aim to enhance reasoning capabilities in complex tasks. However, the security im…