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Weiyuan Li

5 accepted papers

2025

Curse of Knowledge: Your Guidance and Provided Knowledge are biasing LLM Judges in Complex Evaluation

EMNLP 2025

As large language models (LLMs) grow more capable, they face increasingly diverse and complex tasks, making reliable evaluation challenging. The paradigm of LLMs as judges has emerged as a scalable solution, yet prior work primarily focuses on simple settings. Their reliability in complex tasks—wher

Cited by 0SourcePDFScholar
2025

Enhancing Persona Consistency for LLMs’ Role-Playing using Persona-Aware Contrastive Learning

ACL 2025finding

In recent years, large language models (LLMs) have achieved breakthrough progress in many dialogue generation tasks. However, their lack of emotion and fine-grained role awareness limits the model’s ability to provide personalized and diverse interactions further. Current methods face high costs in…

Cited by 0SourcePDFScholar
2025

SmartRAG: Jointly Learn RAG-Related Tasks From the Environment Feedback

ICLR 2025poster

RAG systems consist of multiple modules to work together. However, these modules are usually separately trained. We argue that a system like RAG that incorporates multiple modules should be jointly optimized to achieve optimal performance. To demonstrate this, we design a specific pipeline called Sm…

Cited by 4SourcePDFScholar
2023

Transformer Memory for Interactive Visual Navigation in Cluttered Environments

RA-L 2023

Substantial progress has been achieved in embodied visual navigation based on reinforcement learning (RL). These studies presume that the environment is stationary where all the obstacles are static. However, in real cluttered scenes, interactable objects (e.g. shoes and boxes) blocking the way of r

Cited by 20SourceScholar
2020

DoveNet: Deep Image Harmonization via Domain Verification

CVPR 2020poster

Image composition is an important operation in image processing, but the inconsistency between foreground and background significantly degrades the quality of composite image. Image harmonization, aiming to make the foreground compatible with the background, is a promising yet challenging task. Howe…

Cited by 260PDFcodeScholar