activity
20242026
collaborators

9 papers

cs.SE2026

Beyond Fail-to-Pass: Iterative Hardening of Co-Generated Bug Reproduction Tests and Fixes

Yuhao Tan, Zhibang Yang, Fangkai Yang +9

Large language models (LLMs) have made automated program repair (APR) increasingly practical for real-world bugs, but repairing directly from bug reports remains underconstrained.…

cs.LG2026

InvWeaver: Deductive Feedback for Invariant Synthesis in Interacting-Loop Programs

Guangyuan Wu, Weining Cao, Zehui Tan +4

Loop invariant inference is a fundamental yet challenging problem in program verification. Recent LLM-aided guess-and-check techniques have shown strong performance on single-loop…

cs.CV2026

Omni-DuplexEval: Evaluating Real-time Duplex Omni-modal Interaction

Chaoqun He, Mingyang Xiang, Yingjing Xu +5

Real-time duplex interaction is essential for multimodal AI systems operating in real-world scenarios, where models must continuously process streaming inputs and respond at approp…

cs.CL2026

Full Attention Strikes Back: Transferring Full Attention into Sparse within Hundred Training Steps

Yanke Zhou, Yiduo Li, Hanlin Tang +6

Long-context inference in large language models is bottlenecked by the quadratic cost of full attention. Existing efficient alternatives often rely either on native sparse training…

cs.SE2026

Synthesizing Inductive Invariants for Distributed Protocols via IC3 and Large Language Models

Weining Cao, Guangyuan Wu, Yuan Yao +3

Distributed protocols are notoriously difficult to verify correctly. Proving safety typically requires inductive invariants that both imply the desired property and are preserved b…

cs.SE2026

Task Abstention for Large Language Models in Code Generation

Yanke Zhou, Yuhao Tan, Senrong Xu +4

Large language models (LLMs) have revolutionized automated code generation. One serious concern, however, is the so-called ``hallucination'', i.e., LLMs may generate seemingly plau…