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papers

RedOne 2.0: Rethinking Domain-specific LLM Post-Training in Social
Networking Services

RedOne 2.0: Rethinking Domain-specific LLM Post-Training in Social Networking Services

Supervised Fine-Tuning

Fei Zhao, Chonggang Lu, Haofu Qian, et al.

The Station: An Open-World Environment for AI-Driven Discovery

The Station: An Open-World Environment for AI-Driven Discovery

Stephen Chung, Wenyu Du

DRIVE: Data Curation Best Practices for Reinforcement Learning with
Verifiable Reward in Competitive Code Generation

Supervised Fine-Tuning

Reinforcement Learning

Speed Zhu, Jianwei Cai, Guang Chen, et al.

IterResearch: Rethinking Long-Horizon Agents via Markovian State
Reconstruction

Reinforcement Learning

Guoxin Chen, Zile Qiao, Xuanzhong Chen, et al.

HaluMem: Evaluating Hallucinations in Memory Systems of Agents

Ding Chen, Simin Niu, Kehang Li, et al.

GVPO: Group Variance Policy Optimization for Large Language Model Post-Training

Preference Modeling

Kaichen Zhang, Yuzhong Hong, Junwei Bao, et al.

ReCA: Integrated Acceleration for Real-Time and Efficient Cooperative Embodied Autonomous Agents

Embodied Intelligence

Zishen Wan, Yuhang Du, Mohamed Ibrahim, et al.

DexFlyWheel: A Scalable and Self-improving Data Generation Framework for Dexterous Manipulation

Reinforcement Learning

Kefei Zhu, Fengshuo Bai, YuanHao Xiang, et al.

NovaFlow: Zero-Shot Manipulation via Actionable Flow from Generated Videos

Hongyu Li, Lingfeng Sun, Yafei Hu, et al.

TreeSynth: Synthesizing Diverse Data from Scratch via Tree-Guided Subspace Partitioning

Sheng Wang, Pengan Chen, Jingqi Zhou, et al.

GTA: Supervised-Guided Reinforcement Learning for Text Classification with Large Language Models

Supervised Fine-Tuning

Reinforcement Learning

Ivan Anishchenko, Yakov Kipnis, Indrek Kalvet, et al.

Modeling protein-small molecule conformational ensembles with PLACER

Ivan Anishchenko, Yakov Kipnis, Indrek Kalvet, et al.

Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models

Qizheng Zhang, Changran Hu, Shubhangi Upasani, et al.

DiaMoE-TTS: A Unified IPA-Based Dialect TTS Framework with Mixture-of-Experts and Parameter-Efficient Zero-Shot Adaptation

Ziqi Chen, Gongyu Chen, Yihua Wang, et al.

AI Assisted AR Assembly: Object Recognition and Computer Vision for Augmented Reality Assisted Assembly

Object Detection

Object Recognition

Alexander Htet Kyaw, Haotian Ma, Sasa Zivkovic, et al.

Jailbreaking in the Haystack

Rishi Rajesh Shah, Chen Henry Wu, Shashwat Saxena, et al.

CritiCal: Can Critique Help LLM Uncertainty or Confidence Calibration?

Qing Zong, Jiayu Liu, Tianshi Zheng, et al.

Towards Mitigating Hallucinations in Large Vision-Language Models by
Refining Textual Embeddings

Multimodal Representation

Aakriti Agrawal, Gouthaman KV, Rohith Aralikatti, et al.

Visual Spatial Tuning

Multimodal Representation

Rui Yang, Ziyu Zhu, Yanwei Li, et al.

Too Good to be Bad: On the Failure of LLMs to Role-Play Villains

Zihao Yi, Qingxuan Jiang, Ruotian Ma, et al.

DeepEyesV2: Toward Agentic Multimodal Model

Jack Hong, Chenxiao Zhao, ChengLin Zhu, et al.

Use of Continuous Glucose Monitoring with Machine Learning to Identify Metabolic Subphenotypes and Inform Precision Lifestyle Changes

Ahmed A. Metwally, Heyjun Park, Yue Wu, et al.

Reusing Pre-Training Data at Test Time is a Compute Multiplier

Retrieval-Augmented Generation

Alex Fang, Thomas Voice, Ruoming Pang, et al.

NVIDIA Nemotron Nano V2 VL

NVIDIA, Amala Sanjay Deshmukh, Kateryna Chumachenko, et al.

CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents

Jiayu Liu, Cheng Qian, Zhaochen Su, et al.

Cambrian-S: Towards Spatial Supersensing in Video

Video Understanding

Shusheng Yang, Jihan Yang, Pinzhi Huang, et al.

Scaling Agent Learning via Experience Synthesis

Reinforcement Learning

Zhaorun Chen, Zhuokai Zhao, Kai Zhang, et al.

V-Thinker: Interactive Thinking with Images

Runqi Qiao, Qiuna Tan, Minghan Yang, et al.

Thinking with Video: Video Generation as a Promising Multimodal
Reasoning Paradigm

Video Generation

Jingqi Tong, Yurong Mou, Hangcheng Li, et al.

Recent Developments in Amber Biomolecular Simulations

David A. Case, David S. Cerutti, Vinicius Wilian D. Cruzeiro, et al.

UltraHR-100K: Enhancing UHR Image Synthesis with A Large-Scale High-Quality Dataset

Diffusion Model

Chen Zhao, En Ci, Yunzhe Xu, et al.

From Five Dimensions to Many: Large Language Models as Precise and Interpretable Psychological Profilers

Yi-Fei Liu, Yi-Long Lu, Di He, et al.

DRIVE: Data Curation Best Practices for Reinforcement Learning with Verifiable Reward in Competitive Code Generation

IterResearch: Rethinking Long-Horizon Agents via Markovian State Reconstruction

HaluMem: Evaluating Hallucinations in Memory Systems of Agents

GVPO: Group Variance Policy Optimization for Large Language Model Post-Training

ReCA: Integrated Acceleration for Real-Time and Efficient Cooperative Embodied Autonomous Agents

DexFlyWheel: A Scalable and Self-improving Data Generation Framework for Dexterous Manipulation

NovaFlow: Zero-Shot Manipulation via Actionable Flow from Generated Videos

TreeSynth: Synthesizing Diverse Data from Scratch via Tree-Guided Subspace Partitioning

GTA: Supervised-Guided Reinforcement Learning for Text Classification with Large Language Models

Modeling protein-small molecule conformational ensembles with PLACER

Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models

DiaMoE-TTS: A Unified IPA-Based Dialect TTS Framework with Mixture-of-Experts and Parameter-Efficient Zero-Shot Adaptation

AI Assisted AR Assembly: Object Recognition and Computer Vision for Augmented Reality Assisted Assembly

Jailbreaking in the Haystack

CritiCal: Can Critique Help LLM Uncertainty or Confidence Calibration?

Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings

Visual Spatial Tuning

Too Good to be Bad: On the Failure of LLMs to Role-Play Villains

DeepEyesV2: Toward Agentic Multimodal Model

Use of Continuous Glucose Monitoring with Machine Learning to Identify Metabolic Subphenotypes and Inform Precision Lifestyle Changes

Reusing Pre-Training Data at Test Time is a Compute Multiplier

NVIDIA Nemotron Nano V2 VL

CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents

Cambrian-S: Towards Spatial Supersensing in Video

Scaling Agent Learning via Experience Synthesis

V-Thinker: Interactive Thinking with Images

Thinking with Video: Video Generation as a Promising Multimodal Reasoning Paradigm

Recent Developments in Amber Biomolecular Simulations

UltraHR-100K: Enhancing UHR Image Synthesis with A Large-Scale High-Quality Dataset

From Five Dimensions to Many: Large Language Models as Precise and Interpretable Psychological Profilers

3,011