3 citations · 5 across the 6 of their papers we have counts for
6 papers
Multiple-Choice Questions are Efficient and Robust LLM Evaluators
Ziyin Zhang, Zhaokun Jiang, Lizhen Xu +2
We present GSM-MC, a multiple-choice (MC) dataset constructed by collecting answers and incorrect predictions on GSM8K from 60 open-source models. Through extensive experiments, we…
G-Refine: A General Quality Refiner for Text-to-Image Generation
Chunyi Li, Haoning Wu, Hongkun Hao +7
With the evolution of Text-to-Image (T2I) models, the quality defects of AI-Generated Images (AIGIs) pose a significant barrier to their widespread adoption. In terms of both perce…
Q-Refine: A Perceptual Quality Refiner for AI-Generated Image
Chunyi Li, Haoning Wu, Zicheng Zhang +7
With the rapid evolution of the Text-to-Image (T2I) model in recent years, their unsatisfactory generation result has become a challenge. However, uniformly refining AI-Generated I…
Boosting Large Language Model for Speech Synthesis: An Empirical Study
Hongkun Hao, Long Zhou, Shujie Liu +4
Large language models (LLMs) have made significant advancements in natural language processing and are concurrently extending the language ability to other modalities, such as spee…
Penalty Decoding: Well Suppress the Self-Reinforcement Effect in Open-Ended Text Generation
Wenhong Zhu, Hongkun Hao, Rui Wang
The decoding algorithm is critical for open-ended text generation, transforming latent representations into coherent and meaningful outputs. This paper investigates the self-reinfo…
Rethinking Translation Memory Augmented Neural Machine Translation
Hongkun Hao, Guoping Huang, Lemao Liu +3
This paper rethinks translation memory augmented neural machine translation (TM-augmented NMT) from two perspectives, i.e., a probabilistic view of retrieval and the variance-bias…