Trending Papers - Hugging Face (original) (raw)

new

Get trending papers in your email inbox once a day!

Get trending papers in your email inbox!

Subscribe

byAK and the research community

Submitted by Paper99

Submitted by Paper99

Submitted by Cxxs

Submitted by Cxxs

Submitted by taesiri

Submitted by taesiri

Submitted by Zuica96

Submitted by Zuica96

Submitted by akhaliq

Submitted by akhaliq

Submitted by taesiri

DeepCode: Open Agentic Coding

DeepCode, a fully autonomous framework, addresses the challenges of document-to-codebase synthesis by optimizing information flow through source compression, structured indexing, knowledge injection, and error correction, achieving state-of-the-art performance and surpassing human experts.

· Published on Dec 8, 2025

Submitted by taesiri

DeepCode: Open Agentic Coding

DeepCode, a fully autonomous framework, addresses the challenges of document-to-codebase synthesis by optimizing information flow through source compression, structured indexing, knowledge injection, and error correction, achieving state-of-the-art performance and surpassing human experts.

Submitted by nuojohnchen

Submitted by nuojohnchen

Submitted by taesiri

SAM 3: Segment Anything with Concepts

Segment Anything Model 3 achieves state-of-the-art performance in promptable concept segmentation and tracking by leveraging a unified model architecture with decoupled recognition and localization.

Submitted by taesiri

SAM 3: Segment Anything with Concepts

Segment Anything Model 3 achieves state-of-the-art performance in promptable concept segmentation and tracking by leveraging a unified model architecture with decoupled recognition and localization.

LightRAG: Simple and Fast Retrieval-Augmented Generation

LightRAG improves Retrieval-Augmented Generation by integrating graph structures for enhanced contextual awareness and efficient information retrieval, achieving better accuracy and response times.

· Published on Oct 8, 2024

Submitted by wanderkid

Submitted by wanderkid

Submitted by taesiri

Submitted by taesiri

Submitted by kenshinn

Submitted by kenshinn

Submitted by taesiri

LongCat-Image Technical Report

LongCat-Image is a bilingual open-source foundation model for image generation that addresses multilingual text rendering, photorealism, and deployment efficiency through rigorous data curation, compact design, and comprehensive open-source support.

meituan-longcat LongCat · Published on Dec 8, 2025

Submitted by taesiri

LongCat-Image Technical Report

LongCat-Image is a bilingual open-source foundation model for image generation that addresses multilingual text rendering, photorealism, and deployment efficiency through rigorous data curation, compact design, and comprehensive open-source support.

Submitted by taesiri

Submitted by taesiri

Submitted by Rbin

RAG-Anything: All-in-One RAG Framework

RAG-Anything is a unified framework that enhances multimodal knowledge retrieval by integrating cross-modal relationships and semantic matching, outperforming existing methods on complex benchmarks.

Submitted by Rbin

RAG-Anything: All-in-One RAG Framework

RAG-Anything is a unified framework that enhances multimodal knowledge retrieval by integrating cross-modal relationships and semantic matching, outperforming existing methods on complex benchmarks.

Submitted by RuoyuFeng

Submitted by RuoyuFeng

Submitted by Alicezrzhao

Submitted by Alicezrzhao

Submitted by akhaliq

Submitted by akhaliq

Submitted by akhaliq

Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory

Mem0, a memory-centric architecture with graph-based memory, enhances long-term conversational coherence in LLMs by efficiently extracting, consolidating, and retrieving information, outperforming existing memory systems in terms of accuracy and computational efficiency.

· Published on Apr 28, 2025

Submitted by akhaliq

Submitted by taesiri

SAM 3D: 3Dfy Anything in Images

SAM 3D is a generative model that reconstructs 3D objects from single images using a multi-stage training framework that includes synthetic pretraining and real-world alignment, achieving high performance in human preference tests.

Submitted by taesiri

SAM 3D: 3Dfy Anything in Images

SAM 3D is a generative model that reconstructs 3D objects from single images using a multi-stage training framework that includes synthetic pretraining and real-world alignment, achieving high performance in human preference tests.

Submitted by xandergos

Submitted by xandergos

Submitted by fengerhu

MobiAgent: A Systematic Framework for Customizable Mobile Agents

MobiAgent, a comprehensive mobile agent system, achieves state-of-the-art performance in real-world mobile scenarios through its MobiMind-series models, AgentRR framework, and MobiFlow benchmarking suite, while also reducing data annotation costs.

· Published on Aug 30, 2025

Submitted by fengerhu

Submitted by SereinH

Submitted by SereinH

Submitted by wenyi

Submitted by wenyi

Submitted by AdinaY

Submitted by AdinaY

Submitted by taesiri

Submitted by taesiri

Submitted by Gynjn

Submitted by Gynjn

Submitted by akhaliq

UI-TARS: Pioneering Automated GUI Interaction with Native Agents

UI-TARS, a native GUI agent model using screenshots as input, outperforms commercial models in various benchmarks through enhanced perception, unified action modeling, system-2 reasoning, and iterative training with reflective online traces.

· Published on Jan 21, 2025

Submitted by akhaliq

Submitted by hiyouga

Submitted by hiyouga

Submitted by Weiyun1025

Submitted by Weiyun1025

Submitted by Jeff-Wang

Submitted by Jeff-Wang

Submitted by dyyyyyyyy

Submitted by dyyyyyyyy

Submitted by daixufang

Submitted by daixufang

Submitted by taesiri

Submitted by taesiri

Submitted by KaituoFeng

Submitted by KaituoFeng

Submitted by zhangshaolei

Submitted by zhangshaolei

Submitted by Owen777

Submitted by Owen777

Submitted by gaomingqi

Submitted by gaomingqi

Submitted by Paranioar

Submitted by Paranioar

Submitted by xw-eric

Submitted by xw-eric

Submitted by xw-eric

The Unreasonable Effectiveness of Scaling Agents for Computer Use

Behavior Best-of-N (bBoN) improves the reliability and success rates of computer-use agents by generating and selecting among multiple rollouts using behavior narratives, achieving state-of-the-art performance on OSWorld and strong generalization to different operating systems.

simular-ai Simular · Published on Oct 2, 2025

Submitted by xw-eric

The Unreasonable Effectiveness of Scaling Agents for Computer Use

Behavior Best-of-N (bBoN) improves the reliability and success rates of computer-use agents by generating and selecting among multiple rollouts using behavior narratives, achieving state-of-the-art performance on OSWorld and strong generalization to different operating systems.