3 papers
cs.CV2026
ZeroBench: An Impossible Visual Benchmark for Contemporary Large Multimodal Models
Jonathan Roberts, Mohammad Reza Taesiri, Ansh Sharma +31
Large Multimodal Models (LMMs) exhibit shortfalls when interpreting images and, by some measures, have poorer spatial cognition than young children or animals. Despite this, they a…
cs.CL2026
Surgical Post-Training: Proximal On-Policy Distillation for Reasoning with Knowledge Retention
Wenye Lin, Kai Han
Injecting new reasoning knowledge into Large Language Models (LLMs) via post-training often induces catastrophic forgetting. Recent studies emphasize the importance of on-policy da…
cs.CL2025
GAMEBoT: Transparent Assessment of LLM Reasoning in Games
Wenye Lin, Jonathan Roberts, Yunhan Yang +3
Large Language Models (LLMs) are increasingly deployed in real-world applications that demand complex reasoning. To track progress, robust benchmarks are required to evaluate their…