3 papers
cs.LG2026
Diagnosing JEPA World Models with Action-Conditioned Predictive Consistency
Guo An, Zijing Wu, Honghua Dong +7
Joint-embedding predictive architectures (JEPAs) learn world models that predict in a compact latent space rather than in pixels, reducing the pressure to model nuisance appearance…
cs.CL2026
Confidence Before Answering: A Paradigm Shift for Efficient LLM Uncertainty Estimation
Changcheng Li, Jiancan Wu, Hengheng Zhang +5
Reliable deployment of large language models (LLMs) requires accurate uncertainty estimation. Existing methods are predominantly answer-first, producing confidence only after gener…
cs.CR2026
Learning to Generate Secure Code via Token-Level Rewards
Jiazheng Quan, Xiaodong Li, Bin Wang +5
Large language models (LLMs) have demonstrated strong capabilities in code generation, yet they remain prone to producing security vulnerabilities. Existing approaches commonly suf…