Browsing: Hugging Face
Multi-layer perceptrons (MLPs) conventionally follow a narrow-wide-narrow design where skip connections operate at the input/output dimensions while processing occurs in…
The Transformer architecture, underpinned by the Multi-Head Attention (MHA) mechanism, has become the de facto standard for state-of-the-art models in…
Large language models (LLMs) often generate hallucinations — unsupported content that undermines reliability. While most prior works frame hallucination detection…
Artificial intelligence is undergoing the paradigm shift from closed language models to interconnected agent systems capable of external perception and…
Large language models (LLMs) have recently demonstrated strong capabilities as autonomous agents, showing promise in reasoning, tool use, and sequential…
In arena-style evaluation of large language models (LLMs), two LLMs respond to a user query, and the user chooses the…
Fine-grained visual reasoning remains a core challenge for multimodal large language models (MLLMs). The recently introduced ReasonMap highlights this gap…
Reinforcement learning from verifiable rewards (RLVR) is an emerging paradigm for improving the reasoning ability of large language models. However,…
Computer-use agents (CUAs) hold promise for automating everyday digital tasks, but their unreliability and high variance hinder their application to…
Drag-based image editing has long suffered from distortions in the target region, largely because the priors of earlier base models,…