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Papers
Daily updated cutting-edge AI research papers to help you keep up with the latest AI trends
3,198 papers
Multi-Stream Attention Residuals
Transformer
Deep Learning
Xiaohan Qin, Xiangdong Zhang, Tuo Dai, et al.
VIS-Ground: Video Interactive Storytelling with Contextual Grounding
Video Generation
Multimodal
Bingxuan Li, Yiwen Song, Xueqing Wu, et al.
Thinking Inertia: LLMs Keep Thinking When Told Not To
LLM
Reasoning
Dianqiao Lei, Kevin Qinghong Lin, Pan Lu, et al.
SCALING AGENTIC DATA FOR LONG-HORIZON TERMINAL INTELLIGENCE
Agent
Qwen
Shun Zou, Ziyu Ma, Yi Zou, et al.
GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives
Perception
Multimodal Representation
Qize Yu, Lianrui Fan, Boyu Chen, et al.
AGENTSWE: CAN CODING AGENTS BUILD THE AGENT YOU ACTUALLY WANT?
Code Generation
Agent
Jiahao Wang, Hongjin Qian, Yuyang Hu, et al.
VISIONWEAVE: WEAVING ELASTIC VISUAL REPRESENTATIONS AS A NATIVE CAPABILITY OF MLLMS
Multimodal
Multimodal Representation
Yuan Feng, Qize Yang, Ruizhe Chen, et al.
EmbodiedCLBench: Evaluating Continual Learning for Self-Evolving Embodied Agents
Embodied Intelligence
Agent
Jie Huang, Yanan Chen, Ruixun Liu, et al.
SOFTWAREGYM: SCALING COMPUTER-USE AGENT TRAINING WITH DIVERSE SYNTHESIZED SOFTWARE ENVIRONMENTS
Agent
LLM
Tian Jin, Wenhao Wang, Jing Kang, et al.
Reflex: Visually Grounded Reactive Humanoid Control
Robotics
Reinforcement Learning
Taoyang Jia, Weikai Huang, Linxin Song, et al.
S-Space: Exploring Spatial Workspace in Multimodal Language Models
Multimodal Representation
LLM
Zhiyuan Shi, Xiang Li, Xingzhuo Guo, et al.
DIFFUSIONART: EFFICIENT, STABLE AND SCALABLE REINFORCEMENT OF DIFFUSION MODELS
Diffusion Model
Reinforcement Learning
Zhenglin Wan, Jiayu Chen, Zhengfeiyang Zhang, et al.
MULTI-AGENT EGOCENTRIC WORLD MODEL WITH FINE-GRAINED EMBODIED INTERACTION
World Models
Video Generation
Dahyun Chung, Siyoon Jin, Hyunwook Choi, et al.
SUPERNAV: AN AGENTIC NAVIGATION SYSTEM FOR ANY TASK IN ANY SCENE
Agent
LLM
Jinkai Zhang, Jingyi Xu, Yuanhong Yu, et al.
MiMo-V2.6: Scaling Reinforcement Learning Towards Self-Improvement
Reinforcement Learning
Multimodal
Zongming Qiao, Ziyue Hua, Zirui Ou, et al.
TokenRouter: Efficient Serving System for Token-Level LLM Routing
LLM
Text Generation
Tianyu Fu, Tengxuan Liu, Ruoxi Wang, et al.
AgentGarten: Code Worlds for Evolving Agents
Agent
Reinforcement Learning
Jiawei Chi, Shangchen Miao, Zhiyuan Shi, et al.
From Traces to Agentic Worlds: Agentic Language World Models for Interactive Environment Simulation
World Models
Agent
Quanyu Long, Xiao Chen, Jianda Chen, et al.
H-JEPA: END-TO-END LEARNING OF HIERARCHICAL WORLD MODELS FOR VISUAL PLANNING
World Models
Wancong Zhang, Basile Terver, Michael Rabbat, et al.
ID Balancing: Stable Training of Extremely Sparse MoE via PID-Based Load Control
Model Training
LLM
Peng Jin, Zihan Qiu, Zekun Wang, et al.
GPU-Accelerated Astrodynamics World Models for Spacecraft Rendezvous and Proximity Operations
World Models
Deep Learning
Duncan Eddy, Isaac R. Ward, Grace Ra Kim, et al.
4DCodeBench: Benchmarking Agents on Inverse Graphics of Dynamic Scenes
Code Generation
Video Understanding
Ruihong Shen, Žiga Kovačič, Peter Kulits, et al.
QUESTIONING THE QUESTIONS: SUSTAINING SELF-EVOLUTION IN REASONING MODELS
Reasoning
Code Generation
Jinyuan Li, Chengsong Huang, Langlin Huang, et al.
DECEPEVAL: A BENCHMARK FOR EVALUATING DE-CEPTION IN LLM AGENTS
LLM
Agent
Yiming Xu, Hongyue Yu, Beihua Yang, et al.
nanoMuse: An Open-Source Personal Agent for Every Device You Own
Agent
LLM
Guangyi Liu, Yong Liu, Jiangning Zhang
RECURSIVE GAME CREATOR: AN AGENTIC PRODUCT-LEVEL EXPERIENCE-ORIENTED GAME HARNESS
Agent
Code Generation
Jiajun Chen, Haoyu Wu, Mingda Jia, et al.
Long-WAM: Scaling the Context of World-Action Models
World Models
Video Understanding
Wei Huang, Bohan Zhang, Chenzhi Liu, et al.
STEPQUANT: WHEN AND WHERE ERRORS MATTER IN DELTA-RULE RECURRENT STATE QUANTIZATION
Transformer
LLM
Bingchen Yao, Haobo Xu, Haokun Lin, et al.
WING: World Action Learning via INteraction-Centric Spectral Latent Guidance
Reinforcement Learning
Video Understanding
Zhiming Liu, Yikun Miao, Ying Chen, et al.
FROM EVIDENCE TO ACTION: HOW TOOL-USING AGENTS FAIL
Agent
Reasoning
Hongzhan Lin, Shidong Cao, Ziyang Luo, et al.
EVISKILL: GROUNDING SKILL EVOLUTION IN RE-PLAYABLE EVIDENCE
LLM
Agent
Yan Zhou, Yili Wang, Yiwei Dai, et al.
TRACE: Rollout-Guided Quantization-Aware Training for FP4 Reinforcement Learning of MoE Language Models
Reinforcement Learning
LLM
Xin Wang, Hao Yu, Zhengyang Zhuge, et al.