Papers by Xisheng Xiao
From A and B to A+B: Can Large Language Models Solve Compositional Math Problems? (2025.emnlp-main)
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| Challenge: | Existing studies that create problem variants by adding perturbations to a single problem focus on the interaction between problems. |
| Approach: | They propose a pipeline with 98.2% accuracy to combine two original problems with a logical connection and to evaluate LLMs' generalization ability on the compositional problems. |
| Outcome: | The proposed pipeline can combine two original problems with a logical connection to get a new math problem and evaluate its compositional generalization on the compositional problems. |
DMIN: A Discourse-specific Multi-granularity Integration Network for Conversational Aspect-based Sentiment Quadruple Analysis (2024.findings-acl)
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| Challenge: | Existing studies focus on enhancing token-level interactions, but lack sufficient modeling of discourse structure information. |
| Approach: | They propose to use a discourse structure called "thread" to enhance token interaction among different utterances. |
| Outcome: | The proposed model achieves state-of-the-art on two datasets. |
Logits Reranking via Semantic Labels for Hard Samples in Text Classification (2024.findings-emnlp)
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| Challenge: | Existing research on text classification models ignores the semantic information inherent in labels, treating them as one-hot vectors. |
| Approach: | They propose a model-agnostic method that leverages label semantics and auto detection of hard samples to improve classification accuracy. |
| Outcome: | The proposed method shows significant improvements across different PLMs. |