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From the 3 of 11 linked papers with an AI index.

collaborators

11 papers

cs.LG2026

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

Xingjian Wu, Xuhang Zhu, Xingchen Liu +6

The paper introduces ClawTrack, a benchmark that evaluates both the final outcomes and the step-by-step reasoning processes of LLM-based autonomous agents across multiple dimension…

cs.LG2026

Contrastive Reinforced Policy Optimization via Privileged Self-Distillation

Xingjian Wu, Junlin Liu, Xingchen Liu +6

The paper introduces Contrastive Reinforced Policy Optimization (CRPO), a method that frames on‑policy self‑distillation for large language models as a contrastive learning problem…

cs.IR2026

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

Zhi Chen, Minmao Wang, Xingchen Liu +8

The paper introduces a feedback‑driven framework that first extracts user intent and then discovers recommendation policies using outcome‑derived feedback, distilling this knowledg…

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.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.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…