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Chain-of-thought (CoT) monitoring assumes that reasoning traces faithfully record the information that shapes a model...
Text-to-image models learn associations between concepts - in the case of this paper, people's professions, which we ...
Detecting hallucinations in Large Vision-Language Models (LVLMs) requires both accurate span localization and well-ca...
Multimodal misinformation on social media is highly prevalent, potent, and harmful, yet difficult to detect and count...
Chain-of-thought (CoT) reasoning has dramatically improved large language models (LLMs) by allowing them to decompose...
Long autoregressive video generation faces a fundamental memory challenge: with a finite attention window, a model mu...
AI agents in partially observable environments need to coordinate active sensing with working memory to maintain an e...
Agent working memory is heterogeneous. Objects such as instructions, artifacts, tool outputs, and agent-generated sta...
When a large language model fails a reasoning task, it is often assumed to lack the underlying capability. However, t...
We propose a lightweight two-stage framework for real-time video anomaly detection. The first stage employs YOLO v11n...
Recent advances in large reasoning models (LRMs) have shown that reinforcement learning with verifiable rewards (RLVR...
Autonomous scientific research agents are increasingly applied to end-to-end scientific workflows, including literatu...