1 citations · 2 across the 6 of their papers we have counts for
7 papers
Scalable Weak-to-Strong Verifier Hardening for Agent Environments
Chong Zeng, Ziqian Zhong, Kexun Zhang +5
Agent environments are essential for large language model (LLM) development. They use programmatic verifiers to turn complex outcomes into rewards. Verifiers can be attacked into a…
Hardening Agent Benchmarks with Adversarial Hacker-Fixer Loops
Ziqian Zhong, Ivgeni Segal, Ivan Bercovich +3
Agent benchmarks score submissions with outcome verifiers that are typically hand-written and brittle, leaving them open to reward hacking. We audit 1,968 tasks across five termina…
Terminal Wrench: A Dataset of 331 Reward-Hackable Environments and 3,632 Exploit Trajectories
Ivan Bercovich, Ivgeni Segal, Kexun Zhang +3
We release Terminal Wrench, a subset of 331 terminal-agent benchmark environments, copied from the popular open benchmarks that are demonstrably reward-hackable. The data set inclu…
Is Vibe Coding Safe? Benchmarking Vulnerability of Agent-Generated Code in Real-World Tasks
Songwen Zhao, Danqing Wang, Kexun Zhang +3
Vibe coding is a new software development paradigm in which human engineers prompt a large language model (LLM) agent to complete complex coding tasks with little supervision. Alth…
HardTests: Synthesizing High-Quality Test Cases for LLM Coding
Zhongmou He, Yee Man Choi, Kexun Zhang +6
Verifiers play a crucial role in large language model (LLM) reasoning, needed by post-training techniques such as reinforcement learning. However, reliable verifiers are hard to ge…
Revealing the Barriers of Language Agents in Planning
Jian Xie, Kexun Zhang, Jiangjie Chen +5
Autonomous planning has been an ongoing pursuit since the inception of artificial intelligence. Based on curated problem solvers, early planning agents could deliver precise soluti…
Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents
Kexun Zhang, Weiran Yao, Zuxin Liu +13
Large language model (LLM) agents have shown great potential in solving real-world software engineering (SWE) problems. The most advanced open-source SWE agent can resolve over 27%…