3 citations · 3 across the 8 of their papers we have counts for
8 papers · 1 filter
Calibrated Typed Decisions for Entity, Relation, and Event Extraction
Yang Wang, Hanlin Xiao, Yanan Ma +2
Information extraction models often perform well on the datasets they are trained on, but transferring to new domains and annotation guidelines remains challenging. Supporting user…
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,…
When Tool-Backed Skill Retrieval Fails: Source-Style Collapse in Executable Capability Retrieval
Yiqi Liu, Joseph James, Yang Wang +2
Large-scale agents increasingly rely on retrieval to access external capabilities. We study this retrieval gate in structured tools and APIs, a measurable class of tool-backed exec…
Broken Symmetry in LLM Refusal: Answer Release Is More Local Than Refusal Restoration
Yiqi Liu, Yang Wang, Songxin Wang +2
When a language model refuses to answer a prompt, it is unclear whether the correct answer is erased from its internal representations, or merely suppressed at the output layer. We…
Can LLMs Write Reliable Rubrics? A Meta-Evaluation for Experiment Reproduction
Hanhua Hong, Yizhi Li, Jiaoyan Chen +4
Rubric-based evaluation is a promising approach for assessing open-ended outputs from LLM-based research agents, particularly in paper reproduction, where direct paper-to-repositor…
The Achilles' Heel of Angular Margins: A Chebyshev Polynomial Fix for Speaker Verification
Yang Wang, Yiqi Liu, Chenghao Xiao +1
Angular margin losses, such as AAM-Softmax, have become the de facto in speaker and face verification. Their success hinges on directly manipulating the angle between features and…
RIGOURATE: Quantifying Scientific Exaggeration with Evidence-Aligned Claim Evaluation
Joseph James, Chenghao Xiao, Yucheng Li +2
Scientific rigour tends to be sidelined in favour of bold statements, leading authors to overstate claims beyond what their results support. We present RIGOURATE, a two-stage multi…