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Yuchen Pan

5 accepted papers

2025

Battling against Tough Resister: Strategy Planning with Adversarial Game for Non-collaborative Dialogues

ACL 2025long

Non-collaborative dialogue involves two participants with conflicting interests engaging in a multi-round dialogue to achieve their own goals. Strategy planning is the key to guiding both participants towards a consensus. Most LLMs-based methods use stimulus prompts or external strategy planners for…

2025

FRBNet: Revisiting Low-Light Vision through Frequency-Domain Radial Basis Network

NeurIPS 2025poster

Low-light vision remains a fundamental challenge in computer vision due to severe illumination degradation, which significantly affects the performance of downstream tasks such as detection and segmentation. While recent state-of-the-art methods have improved performance through invariant feature le…

Cited by 0SourcecodeScholar
2024

F2RL: Factuality and Faithfulness Reinforcement Learning Framework for Claim-Guided Evidence-Supported Counterspeech Generation

EMNLP 2024main

Hate speech (HS) on social media exacerbates misinformation and baseless prejudices. Evidence-supported counterspeech (CS) is crucial for correcting misinformation and reducing prejudices through facts. Existing methods for generating evidence-supported CS often lack clear guidance with a core claim…

2024

Intent-Aware and Hate-Mitigating Counterspeech Generation via Dual-Discriminator Guided LLMs

COLING 2024main

Counterspeech is an effective way to combat online hate speech. Considering the multifaceted nature of online hate speech, counterspeech with varying intents (e.g., denouncing or empathy) has significant potential to mitigate hate speech effectively. Recently, controlled approaches based on large la…

Cited by 5SourcePDFScholar
2024

OpticalDR: A Deep Optical Imaging Model for Privacy-Protective Depression Recognition

CVPR 2024poster

Depression Recognition (DR) poses a considerable challenge especially in the context of the growing concerns surrounding privacy. Traditional automatic diagnosis of DR technology necessitates the use of facial images undoubtedly expose the patient identity features and poses privacy risks. In order…