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Wenqiang Li

7 accepted papers

2026

Scope Delineation Before Localization: A Two-Stage Framework for Enhancing Failure Attribution in Multi-Agent Systems

AAAI 2026technical

Large language models (LLMs) are seeing growing adoption in multi-agent systems. In these systems, efficient failure attribution is critical for ensuring robustness and interpretability. Current LLM-based attribution methods often face challenges with lengthy logs and lacking expert knowledge. Drawi

Cited by 0SourcePDFScholar
2025

An Attribute-Enriched Dataset and Auto-Annotated Pipeline for Open Detection

ICASSP 2025accepted

Detecting objects of interest through language often presents challenges, particularly with objects that are uncommon or complex to describe, due to perceptual discrepancies between automated models and human annotators. These challenges highlight the need for comprehensive datasets that go beyond s…

Cited by 0SourceScholar
2025

Conditional Visual Autoregressive Modeling for Pathological Image Restoration

ICCV 2025poster

Pathological image has been recognized as the gold standard for cancer diagnosis for more than a century. However, some internal regions of pathological images may inevitably exhibit various degradation issues, including low resolution, image blurring, and image noising, which will affect disease di…

2025

Meta-Reflection: A Feedback-Free Reflection Learning Framework

ACL 2025long

Despite the remarkable capabilities of large language models (LLMs) in natural language understanding and reasoning, they often display undesirable behaviors, such as generating hallucinations and unfaithful reasoning. A prevalent strategy to mitigate these issues is the use of reflection, which ref…

2024

A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data

ICML 2024poster

Symbolic regression (SR) is a powerful technique for discovering the underlying mathematical expressions from observed data. Inspired by the success of deep learning, recent deep generative SR methods have shown promising results. However, these methods face difficulties in processing high-dimension…

2023

Transformer-based model for symbolic regression via joint supervised learning

ICLR 2023poster

Symbolic regression (SR) is an important technique for discovering hidden mathematical expressions from observed data. Transformer-based approaches have been widely used for machine translation due to their high performance, and are recently highly expected to be used for SR. They input the data poi…

Cited by 28SourcePDFScholar