259 citations · 1.2k across the 111 of their papers we have counts for
16 papers · 1 filter
FrontierCS: Evolving Challenges for Evolving Intelligence
Qiuyang Mang, Wenhao Chai, Zhifei Li +48
We introduce FrontierCS, a benchmark of 156 open-ended problems across diverse areas of computer science, designed and reviewed by experts, including CS PhDs and top-tier competiti…
MURMUR: Using cross-user chatter to break collaborative language agents in groups
Atharv Singh Patlan, Peiyao Sheng, S. Ashwin Hebbar +2
Language agents are rapidly expanding from single-user assistants to multi-user collaborators in shared workspaces and groups. However, today's language models lack a mechanism for…
Benchmarking is Broken -- Don't Let AI be its Own Judge
Zerui Cheng, Stella Wohnig, Ruchika Gupta +13
The meteoric rise of AI, with its rapidly expanding market capitalization, presents both transformative opportunities and critical challenges. Chief among these is the urgent need…
TAO: Tolerance-Aware Optimistic Verification for Floating-Point Neural Networks
Jianzhu Yao, Hongxu Su, Taobo Liao +4
Neural networks increasingly run on hardware outside the user's control (cloud GPUs, inference marketplaces). Yet ML-as-a-Service reveals little about what actually ran or whether…
Are Robust LLM Fingerprints Adversarially Robust?
Anshul Nasery, Edoardo Contente, Alkin Kaz +2
Model fingerprinting has emerged as a promising paradigm for claiming model ownership. However, robustness evaluations of these schemes have mostly focused on benign perturbations…
AutoCode: LLMs as Problem Setters for Competitive Programming
Shang Zhou, Zihan Zheng, Kaiyuan Liu +18
Writing competitive programming problems is exacting. Authors must: set constraints, input distributions, and edge cases that rule out shortcuts; target specific algorithms (e.g.,…