activity
20232025
most citedImproving Factual Consistency of News Summarization by Contrastive Preference Optimization

4 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2025

OmniCharacter: Towards Immersive Role-Playing Agents with Seamless Speech-Language Personality Interaction

Haonan Zhang, Run Luo, Xiong Liu +10

Role-Playing Agents (RPAs), benefiting from large language models, is an emerging interactive AI system that simulates roles or characters with diverse personalities. However, exis…

cs.CL2025

Act-Adaptive Margin: Dynamically Calibrating Reward Models for Subjective Ambiguity

Feiteng Fang, Dingwei Chen, Xiang Huang +10

Currently, most reinforcement learning tasks focus on domains like mathematics and programming, where verification is relatively straightforward. However, in subjective tasks such…

cs.CL2025

OpenOmni: Advancing Open-Source Omnimodal Large Language Models with Progressive Multimodal Alignment and Real-Time Self-Aware Emotional Speech Synthesis

Run Luo, Ting-En Lin, Haonan Zhang +10

Recent advancements in omnimodal learning have significantly improved understanding and generation across images, text, and speech, yet these developments remain predominantly conf…

cs.CL2024★ 1 cited

MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct

Run Luo, Haonan Zhang, Longze Chen +13

The development of Multimodal Large Language Models (MLLMs) has seen significant advancements with increasing demands in various fields (e.g., multimodal agents, embodied intellige…

cs.CL2023★ 4 cited

Improving Factual Consistency of News Summarization by Contrastive Preference Optimization

Huawen Feng, Yan Fan, Xiong Liu +6

Despite the recent progress in news summarization made by large language models (LLMs), they often generate summaries that are factually inconsistent with original articles, known…