5 papers
Stateful Online Monitoring Catches Distributed Agent Attacks
Davis Brown, Samarth Bhargav, Arav Santhanam +7
Language models can find thousands of severe software vulnerabilities, and agents are increasingly being misused for cyberattacks. To avoid detection, attackers frequently distribu…
Benchmarking Misuse Mitigation Against Covert Adversaries
Davis Brown, Mahdi Sabbaghi, Luze Sun +4
Existing language model safety evaluations focus on overt attacks and low-stakes tasks. In reality, an attacker can easily subvert existing safeguards by requesting help on small,…
Detecting Safety Violations Across Many Agent Traces
Adam Stein, Davis Brown, Hamed Hassani +2
To identify safety violations, auditors often search over large sets of agent traces. This search is difficult because failures are often rare, complex, and sometimes even adversar…
BrowserArena: Evaluating LLM Agents on Real-World Web Navigation Tasks
Sagnik Anupam, Davis Brown, Shuo Li +3
LLM web agents now browse and take actions on the open web, yet current agent evaluations are constrained to sandboxed environments or artificial tasks. We introduce BrowserArena,…
Adaptively profiling models with task elicitation
Davis Brown, Prithvi Balehannina, Helen Jin +3
Language model evaluations often fail to characterize consequential failure modes, forcing experts to inspect outputs and build new benchmarks. We introduce task elicitation, a met…