19 citations · 21 across the 14 of their papers we have counts for
15 papers
Disagreeing Rationales: Rethinking Classification and Explainability Evaluation in Hate Speech Detection
Benedetta Muscato, Beiduo Chen, Gizem Gezici +2
Human disagreement is ubiquitous and well-known in labeling. However, variation in explanations, captured through token-level human rationales, remains far less explored. At the sa…
Reasoning that Travels: Dissecting How Chain-of-Thought Transfers Across Models
Xinyuan Cheng, Beiduo Chen, Philipp Mondorf +1
Large reasoning models (LRMs) often generate extensive chain-of-thought (CoT) traces before producing a final answer. As explicit textual artifacts, these traces can be passed to o…
Human Label Variation as Stable Signal: Learning Annotator-Specific Explanation Behavior via Cross-Annotator Preference Optimization
Beiduo Chen, Pingjun Hong, Ziyun Zhang +3
Free-text explanations extend human label variation (HLV) beyond label disagreement by revealing the reasoning and preferences behind annotators' decisions. We study whether large…
Decoupling the Effect of Chain-of-Thought Reasoning: A Human Label Variation Perspective
Beiduo Chen, Tiancheng Hu, Caiqi Zhang +3
Reasoning-tuned LLMs utilizing long Chain-of-Thought (CoT) excel at single-answer tasks, yet their ability to model Human Label Variation--which requires capturing probabilistic am…
Agree, Disagree, Explain: Decomposing Human Label Variation in NLI through the Lens of Explanations
Pingjun Hong, Beiduo Chen, Siyao Peng +3
Natural Language Inference (NLI) datasets often exhibit human label variation. To better understand these variations, explanation-based approaches analyze the underlying reasoning…
Threading the Needle: Reweaving Chain-of-Thought Reasoning to Explain Human Label Variation
Beiduo Chen, Yang Janet Liu, Anna Korhonen +1
The recent rise of reasoning-tuned Large Language Models (LLMs)--which generate chains of thought (CoTs) before giving the final answer--has attracted significant attention and off…
LiTEx: A Linguistic Taxonomy of Explanations for Understanding Within-Label Variation in Natural Language Inference
Pingjun Hong, Beiduo Chen, Siyao Peng +2
There is increasing evidence of Human Label Variation (HLV) in Natural Language Inference (NLI), where annotators assign different labels to the same premise-hypothesis pair. Howev…
MAKIEval: A Multilingual Automatic WiKidata-based Framework for Cultural Awareness Evaluation for LLMs
Raoyuan Zhao, Beiduo Chen, Barbara Plank +1
Large language models (LLMs) are used globally across many languages, but their English-centric pretraining raises concerns about cross-lingual disparities for cultural awareness,…
A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI
Beiduo Chen, Siyao Peng, Anna Korhonen +1
Disagreement in human labeling is ubiquitous, and can be captured in human judgment distributions (HJDs). Recent research has shown that explanations provide valuable information f…
"Seeing the Big through the Small": Can LLMs Approximate Human Judgment Distributions on NLI from a Few Explanations?
Beiduo Chen, Xinpeng Wang, Siyao Peng +3
Human label variation (HLV) is a valuable source of information that arises when multiple human annotators provide different labels for valid reasons. In Natural Language Inference…
Pre-training Language Model as a Multi-perspective Course Learner
Beiduo Chen, Shaohan Huang, Zihan Zhang +6
ELECTRA, the generator-discriminator pre-training framework, has achieved impressive semantic construction capability among various downstream tasks. Despite the convincing perform…
WIDER & CLOSER: Mixture of Short-channel Distillers for Zero-shot Cross-lingual Named Entity Recognition
Jun-Yu Ma, Beiduo Chen, Jia-Chen Gu +5
Zero-shot cross-lingual named entity recognition (NER) aims at transferring knowledge from annotated and rich-resource data in source languages to unlabeled and lean-resource data…
Feature Aggregation in Zero-Shot Cross-Lingual Transfer Using Multilingual BERT
Beiduo Chen, Wu Guo, Quan Liu +1
Multilingual BERT (mBERT), a language model pre-trained on large multilingual corpora, has impressive zero-shot cross-lingual transfer capabilities and performs surprisingly well o…
USTC-NELSLIP at SemEval-2022 Task 11: Gazetteer-Adapted Integration Network for Multilingual Complex Named Entity Recognition
Beiduo Chen, Jun-Yu Ma, Jiajun Qi +3
This paper describes the system developed by the USTC-NELSLIP team for SemEval-2022 Task 11 Multilingual Complex Named Entity Recognition (MultiCoNER). We propose a gazetteer-adapt…
Multi-Level Contrastive Learning for Cross-Lingual Alignment
Beiduo Chen, Wu Guo, Bin Gu +2
Cross-language pre-trained models such as multilingual BERT (mBERT) have achieved significant performance in various cross-lingual downstream NLP tasks. This paper proposes a multi…