11 papers
OVIG: Optimistic Verification of AI Training Integrity via Gradient Signals
Hongxu Su, Jianzhu Yao, Huan Zhang +2
The rapid growth of AI has increased the demand for domain-specific post-training, while the cost and specialization of accelerator infrastructure push many model owners to outsour…
Crypto x AI, AI x Crypto: A Survey
Sarah Allen, Pranay Anchuri, James Austgen +23
The intersection of crypto x AI is spawning papers, products, online posts, and companies. All the surrounding buzz, though, obscures what exactly has been done, what the opportuni…
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…
MINDGAMES: A Live Arena for Evaluating Social and Strategic Reasoning in Multi-Agent LLMs
Kevin Wang, Anna Thöni, Benjamin Kempinski +50
Large language models (LLMs) are increasingly deployed as interactive agents, yet their capacity for social and strategic reasoning over extended interaction remains poorly underst…
MEMO: Memory-Augmented Model Context Optimization for Robust Multi-Turn Multi-Agent LLM Games
Yunfei Xie, Kevin Wang, Bobby Cheng +9
Multi-turn, multi-agent LLM game evaluations often exhibit substantial run-to-run variance. In long-horizon interactions, small early deviations compound across turns and are ampli…
TabularMath: Evaluating Computational Extrapolation in Tabular Learning via Program-Verified Synthesis
Zerui Cheng, Jiashuo Liu, Jianzhu Yao +3
Standard tabular benchmarks mainly focus on the evaluation of a model's capability to interpolate values inside a data manifold, where models good at performing local statistical s…