6 citations · 9 across the 8 of their papers we have counts for
7 papers · 1 filter
Rate-Resolved Text Evaluation with Masked Diffusion Language Models
Yiqi Liu, Kun Zhao, Chenghua Lin +1
A single evaluation score can rank generation systems but rarely reveals what failed. We propose rate-resolved text evaluation, which turns the masking rate of masked diffusion lan…
Feedback as an Interface: Controlling Form and Detail in LLM Translation Refinement
Yiqi Liu, Flavjo Tomori, Nafise Sadat Moosavi +2
Feedback presentation shapes how LLMs use evaluator judgments during translation refinement. We introduce a machine translation protocol that keeps the evaluator score, main issue,…
AutoDataBench: A Data-centric Testbed for Accelerating Auto Research
Ruifeng Yuan, Yizhi Li, Yaxin Du +9
Existing auto-research benchmarks often entangle multiple sources of improvement, including training frameworks, hyperparameters, compute budgets, and data, making it difficult to…
Reading Between the Frames of Multimodal Drivelology
Yang Wang, Yanan Ma, Yiqi Liu +8
Social media videos often communicate meanings that go beyond their visible actions, captions, or speech. A mundane clip may become humorous, ironic, or satire only through the int…
Beyond One-Size-Fits-All: Inversion Learning for Highly Effective NLG Evaluation Prompts
Hanhua Hong, Chenghao Xiao, Yang Wang +3
Evaluating natural language generation systems is challenging due to the diversity of valid outputs. While human evaluation is the gold standard, it suffers from inconsistencies, l…
ContrastScore: Towards Higher Quality, Less Biased, More Efficient Evaluation Metrics with Contrastive Evaluation
Xiao Wang, Daniil Larionov, Siwei Wu +4
Evaluating the quality of generated text automatically remains a significant challenge. Conventional reference-based metrics have been shown to exhibit relatively weak correlation…
LLMs as Narcissistic Evaluators: When Ego Inflates Evaluation Scores
Yiqi Liu, Nafise Sadat Moosavi, Chenghua Lin
Automatic evaluation of generated textual content presents an ongoing challenge within the field of NLP. Given the impressive capabilities of modern language models (LMs) across di…