ClinHallu: A Benchmark for Diagnosing Stage-Wise Hallucinations in Medical MLLM Reasoning
Building trustworthy medical multimodal large language models (MLLMs) is critical for reliable clinical decision supp...
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Building trustworthy medical multimodal large language models (MLLMs) is critical for reliable clinical decision supp...
World models that capture how actions induce physical change enable scalable robot learning without reliance on embod...
AI agent performance depends critically on the runtime harness, comprising the prompts, tools, memory, and control fl...
In this report, we present Hy-Embodied-0.5-VLA, abbreviated as HyVLA-0.5, an end-to-end system that spans the full ro...
Generating avatar videos that are not merely visually similar to a target individual but behaviorally recognizable, f...
The recent success of agent swarms has shifted the paradigm of large language model (LLM)-based agents from single-ag...
Coding agents powered by large language models have demonstrated strong performance on software engineering tasks. Ye...
Large language models (LLMs) are widely used in text-to-image (T2I) systems, but they are typically limited to text e...
Cloning camera motion from reference videos is an important task in video generation, as videos provide intuitive and...
Recent advancements in video-based world models have demonstrated an unprecedented ability to synthesize high-fidelit...
Users rely on execution traces to observe agent behavior, diagnose failures, and ensure accountability. These traces ...
Video generation models based on Diffusion Transformers (DiTs) have achieved remarkable performance in video synthesi...