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Haitian Liu

3 accepted papers

2026

Motus: A Unified Latent Action World Model

CVPR 2026

While a general embodied agent must function as a unified system, current methods are built on isolated models for understanding, world modeling, and control. This fragmentation prevents unifying multimodal generative capabilities and hinders learning from large-scale, heterogeneous data. In this pa

Cited by 0SourcecodeScholar
2025

ClinicalLab: Aligning Agents for Multi-Departmental Clinical Diagnostics in the Real World

NeurIPS 2025poster

Large language models (LLMs) have achieved significant performance progress in various natural language processing applications. However, LLMs still struggle to meet the strict requirements for accuracy and reliability in the medical field and face many challenges in clinical applications. Existing…

Cited by 0SourcecodeScholar
2024

CodeScope: An Execution-based Multilingual Multitask Multidimensional Benchmark for Evaluating LLMs on Code Understanding and Generation

ACL 2024long

Large Language Models (LLMs) have demonstrated remarkable performance on assisting humans in programming and facilitating programming automation. However, existing benchmarks for evaluating the code understanding and generation capacities of LLMs suffer from severe limitations. First, most benchmark…