1 citations · 2 across the 14 of their papers we have counts for
14 papers
MTAVG-Bench 2.0: Diagnosing Failure Modes of Cinematic Expressiveness in Multi-Talker Audio-Video Generation
Haitian Li, Yanghao Zhou, Heyan Huang +15
In recent years, Multi-Talker Audio-Video Generation (MTAVG) models have shown promising performance on fundamental metrics such as lip-sync and audio-visual alignment. However, th…
MTAVG-Bench: A Diagnostic Benchmark for Multi-Talker Dialogue-Centric Audio-Video Generation
Yang-Hao Zhou, Haitian Li, Rexar Lin +12
Recent advances in text-to-audio-video (T2AV) generation have enabled models to synthesize audio-visual videos with multi-participant dialogues. However, existing evaluation benchm…
DeepSurvey-Bench: Evaluating Academic Value of Automatically Generated Scientific Surveys
Guo-Biao Zhang, Xian-Ling Mao, Ding-Yuan Liu +4
The rapid development of automated survey generation technology has made it increasingly important to establish a comprehensive benchmark to evaluate the quality of generated surve…
MMWOZ: Building Multimodal Agent for Task-oriented Dialogue
Pu-Hai Yang, Heyan Huang, Heng-Da Xu +3
Task-oriented dialogue systems have garnered significant attention due to their conversational ability to accomplish goals, such as booking airline tickets for users. Traditionally…
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…
SEOE: A Scalable and Reliable Semantic Evaluation Framework for Open Domain Event Detection
Yi-Fan Lu, Xian-Ling Mao, Tian Lan +3
Automatic evaluation for Open Domain Event Detection (ODED) is a highly challenging task, because ODED is characterized by a vast diversity of un-constrained output labels from var…
A Distributed Collaborative Retrieval Framework Excelling in All Queries and Corpora based on Zero-shot Rank-Oriented Automatic Evaluation
Tian-Yi Che, Xian-Ling Mao, Chun Xu +4
Numerous retrieval models, including sparse, dense and llm-based methods, have demonstrated remarkable performance in predicting the relevance between queries and corpora. However,…
Automatic Evaluation for Text-to-image Generation: Task-decomposed Framework, Distilled Training, and Meta-evaluation Benchmark
Rong-Cheng Tu, Zi-Ao Ma, Tian Lan +3
Driven by the remarkable progress in diffusion models, text-to-image generation has made significant strides, creating a pressing demand for automatic quality evaluation of generat…
Multi-modal Retrieval Augmented Multi-modal Generation: Datasets, Evaluation Metrics and Strong Baselines
Zi-Ao Ma, Tian Lan, Rong-Cheng Tu +6
We present a systematic investigation of Multi-modal Retrieval Augmented Multi-modal Generation (MRAG), a novel task that enables foundation models to process multi-modal web c…
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…
Mix-Initiative Response Generation with Dynamic Prefix Tuning
Yuxiang Nie, Heyan Huang, Xian-Ling Mao +1
Mixed initiative serves as one of the key factors in controlling conversation directions. For a speaker, responding passively or leading proactively would result in rather differen…
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…