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Xiaoman Wang

9 accepted papers

2026

DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving

ICLR 2026poster

Scaling Vision-Language-Action (VLA) models on large-scale data offers a promising path to achieving a more generalized driving intelligence. However, VLA models are limited by a ``supervision deficit'': the vast model capacity is supervised by sparse, low-dimensional actions, leaving much of their…

Cited by 0SourcecodeScholar
2026

DynVLA: Learning World Dynamics for Action Reasoning in Autonomous Driving

ICML 2026poster

We propose DynVLA, a driving VLA model that introduces a new CoT paradigm termed Dynamics CoT. DynVLA forecasts compact world dynamics before action generation, enabling more informed and physically grounded decision-making. To obtain compact dynamics representations, DynVLA introduces a Dynamics To…

Cited by 0SourceScholar
2026

From Interactions to Principles: Experience-Driven Self-Distillation for Evolving LLM Agents

ICML 2026poster

LLM agents have achieved strong performance in tool-augmented reasoning, but most remain largely stateless: after each episode, the agent discards interaction traces and does not accumulate reusable strategies. Prior work either stores raw trajectories for case-based reuse or relies on external teac…

Cited by 0SourceScholar
2026

Interleaving Reasoning for Better Text-to-Image Generation

ICLR 2026poster

Unified multimodal understanding and generation models recently have achieve significant improvement in image generation capability, yet a large gap remains in instruction following and detail preservation compared to systems that tightly couple comprehension with generation such as GPT-4o. Motivate…

Cited by 0SourcecodeScholar
2026

LeanRAG: Knowledge-Graph-Based Generation with Semantic Aggregation and Hierarchical Retrieval

AAAI 2026technical

Retrieval-Augmented Generation (RAG) plays a crucial role in grounding Large Language Models by leveraging external knowledge, whereas the effectiveness is often compromised by the retrieval of contextually flawed or incomplete information. To address this, knowledge graph-based RAG methods have evo

Cited by 0SourcePDFScholar
2025

A Syntactic Approach to Computing Complete and Sound Abstraction in the Situation Calculus

AAAI 2025technical

Abstraction is an important and useful concept in the field of artificial intelligence. To the best of our knowledge, there is no syntactic method to compute a sound and complete abstraction from a given low-level basic action theory and a refinement mapping. This paper aims to address this issue. T…

Cited by 0SourcePDFScholar
2025

UnifiedGEC: Integrating Grammatical Error Correction Approaches for Multi-languages with a Unified Framework

COLING 2025system demonstrations

Grammatical Error Correction is an important research direction in NLP field. Although many models of different architectures and datasets across different languages have been developed to support the research, there is a lack of a comprehensive evaluation on these models, and different architecture…

2020

Assembly of randomly placed parts realized by using only one robot arm with a general parallel-jaw gripper

ICRA 2020poster

In industry assembly lines, parts feeding machines are widely employed as the prologue of the whole procedure. They play the role of sorting the parts randomly placed in bins to the state with specified pose. With the help of the parts feeding machines, the subsequent assembly processes by robot arm…

Cited by 14SourceScholar