3 citations · 4 across the 5 of their papers we have counts for
5 papers
SeedSmith: LLM-Driven Seed Synthesis for Directed Fuzzing
Junmin Zhu, Siyu Liu, Jie Hu +7
Directed fuzzing steers fuzzers toward user-defined sink functions to identify vulnerabilities, but it frequently fails to trigger crashes even after long campaigns. We identify tw…
Root-Cause-Driven Automated Vulnerability Repair
Hulin Wang, Zion Leonahenahe Basque, Jie Hu +13
Recent LLM-based systems have made automated vulnerability repair increasingly practical, but two challenges remain. First, without strong signals about where a bug originates, rep…
BuildBench: Benchmarking LLM Agents on Compiling Real-World Open-Source Software
Zehua Zhang, Ati Priya Bajaj, Divij Handa +14
Automatically compiling open-source software (OSS) projects is a vital, labor-intensive, and complex task, which makes it a good challenge for LLM Agents. Existing methods rely on…
FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks
Bill Yuchen Lin, Chaoyang He, Zihang Zeng +7
Increasing concerns and regulations about data privacy and sparsity necessitate the study of privacy-preserving, decentralized learning methods for natural language processing (NLP…
Do People Prefer "Natural" code?
Casey Casalnuovo, Kevin Lee, Hulin Wang +2
Natural code is known to be very repetitive (much more so than natural language corpora); furthermore, this repetitiveness persists, even after accounting for the simpler syntax of…