activity
20242026
most citedJailbreaking LLM-Controlled Robots

4 citations · 4 across the 6 of their papers we have counts for

collaborators

11 papers

cs.AI2026

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…

cs.RO2026

Contextual Safety Reasoning and Grounding for Open-World Robots

Zachary Ravichandran, David Snyder, Alexander Robey +3

Robots are increasingly operating in open-world environments where safe behavior depends on context: the same hallway may require different navigation strategies when crowded versu…

cs.AI2025

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,…

cs.LG2025

Conformal Information Pursuit for Interactively Guiding Large Language Models

Kwan Ho Ryan Chan, Yuyan Ge, Edgar Dobriban +2

A significant use case of instruction-finetuned Large Language Models (LLMs) is to solve question-answering tasks interactively. In this setting, an LLM agent is tasked with making…

cs.RO2025

Adversarial Attacks on Robotic Vision Language Action Models

Eliot Krzysztof Jones, Alexander Robey, Andy Zou +5

The emergence of vision-language-action models (VLAs) for end-to-end control is reshaping the field of robotics by enabling the fusion of multimodal sensory inputs at the billion-p…

cs.CR2025

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,…