1 citations · 1 across the 8 of their papers we have counts for
8 papers
ISExplore:Informative Segment Selection for Efficient Personalized 3D Talking Face Generation
Rui-Qing Sun, Ang Li, Zhijing Wu +5
Talking Face Generation (TFG) methods based on Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have recently achieved impressive progress in personalized talking hea…
First, Do No Harm: AI Supervisor Scaffolds Novice Growth in Counselor Education
Chen Xu, Zhenyu Lyu, Tian Lan +12
The most dangerous mistakes a novice counselor makes are not the obvious ones: they are utterances that sound caring while quietly violating professional ethics and leaving vulnera…
A Survey of Automatic Evaluation Methods on Text, Visual and Speech Generations
Tian Lan, Yang-Hao Zhou, Zi-Ao Ma +8
Recent advances in deep learning have significantly enhanced generative AI capabilities across text, images, and audio. However, automatically evaluating the quality of these gener…
T2I-Eval-R1: Reinforcement Learning-Driven Reasoning for Interpretable Text-to-Image Evaluation
Zi-Ao Ma, Tian Lan, Rong-Cheng Tu +5
The rapid progress in diffusion-based text-to-image (T2I) generation has created an urgent need for interpretable automatic evaluation methods that can assess the quality of genera…
Training Language Models to Critique With Multi-agent Feedback
Tian Lan, Wenwei Zhang, Chengqi Lyu +6
Critique ability, a meta-cognitive capability of humans, presents significant challenges for LLMs to improve. Recent works primarily rely on supervised fine-tuning (SFT) using crit…
Beyond Exact Match: Semantically Reassessing Event Extraction by Large Language Models
Yi-Fan Lu, Xian-Ling Mao, Tian Lan +3
Event extraction has gained extensive research attention due to its broad range of applications. However, the current mainstream evaluation method for event extraction relies on to…
DECIDER: A Dual-System Rule-Controllable Decoding Framework for Language Generation
Chen Xu, Tian Lan, Yu Ji +8
Constrained decoding approaches aim to control the meaning or style of text generated by the pre-trained large language models (LLMs or also PLMs) for various tasks at inference ti…
CriticEval: Evaluating Large Language Model as Critic
Tian Lan, Wenwei Zhang, Chen Xu +4
Critique ability, i.e., the capability of Large Language Models (LLMs) to identify and rectify flaws in responses, is crucial for their applications in self-improvement and scalabl…