collaborators

12 papers

cs.LG2026

ClawTrack: Towards Trace-Level Evaluation and Improvement of Real-World Autonomous Agents

Xingjian Wu, Xuhang Zhu, Xingchen Liu +6

As LLM-based agents are deployed in complex, multi-step workflows, a critical evaluation gap has emerged: most existing benchmarks judge only final outcomes, unable to distinguish…

cs.LG2026

Contrastive Reinforced Policy Optimization via Privileged Self-Distillation

Xingjian Wu, Junlin Liu, Xingchen Liu +6

Recent advances in post-training Large Language Models (LLMs) increasingly rely on Reinforcement Learning with Verifiable Rewards (RLVR) or On-Policy Self-Distillation (OPSD). Whil…

cs.IR2026

From Understanding to Action: Feedback-Grounded Policy Discovery for Generative Recommendation

Zhi Chen, Minmao Wang, Xingchen Liu +8

Semantic-ID-based generative recommenders enable efficient next-item generation, but their item-level supervision mainly captures behavioral co-occurrence and local transitions. La…

cs.HC2026

AlphaOracle: Oracle bone script decipherment via human-workflow-inspired deep learning

Yuliang Liu, Haisu Guan, Pengjie Wang +11

Approximately 3,000 of the 4,500 oracle bone script (OBS) characters remain undeciphered due to fragmentary inscriptions and sparse evidence. Current AI approaches fail to replicat…

cs.IR2026

OneReason Technical Report

OneRec Team, Biao Yang, Boyang Ding +81

Generative recommendation models in the OneRec family have been widely deployed in many real-world services, such as short-video, live-streaming, advertising, and e-commerce. Howev…

cs.CL2026

DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

DeepSeek-AI, Anyi Xu, Bangcai Lin +315

We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…

cs.AI2026

DocSeeker: Structured Visual Reasoning with Evidence Grounding for Long Document Understanding

Hao Yan, Yuliang Liu, Xingchen Liu +5

Existing Multimodal Large Language Models (MLLMs) suffer from significant performance degradation on the long document understanding task as document length increases. This stems f…

cs.AI2026

LongCat-Flash-Thinking-2601 Technical Report

Meituan LongCat Team, Anchun Gui, Bei Li +162

We introduce LongCat-Flash-Thinking-2601, a 560-billion-parameter open-source Mixture-of-Experts (MoE) reasoning model with superior agentic reasoning capability. LongCat-Flash-Thi…

cs.IR2025

Hierarchical Semantic RL: Tackling the Problem of Dynamic Action Space for RL-based Recommendations

Minmao Wang, Xingchen Liu, Shijie Yi +5

Recommender Systems (RS) are fundamental to modern online services. While most existing approaches optimize for short-term engagement, recent work has begun to explore reinforcemen…

cs.CV2025

VisuRiddles: Fine-grained Perception is a Primary Bottleneck for Multimodal Large Language Models in Abstract Visual Reasoning

Hao Yan, Xingchen Liu, Hao Wang +11

Recent strides in multimodal large language models (MLLMs) have significantly advanced their performance in many reasoning tasks. However, Abstract Visual Reasoning (AVR) remains a…

cs.CV2025

TASTE-Rob: Advancing Video Generation of Task-Oriented Hand-Object Interaction for Generalizable Robotic Manipulation

Hongxiang Zhao, Xingchen Liu, Mutian Xu +3

We address key limitations in existing datasets and models for task-oriented hand-object interaction video generation, a critical approach of generating video demonstrations for ro…

cs.CV2025

UnCommon Objects in 3D

Xingchen Liu, Piyush Tayal, Jianyuan Wang +10

We introduce Uncommon Objects in 3D (uCO3D), a new object-centric dataset for 3D deep learning and 3D generative AI. uCO3D is the largest publicly-available collection of high-reso…