Papers by Zhaorun Chen

2 papers
AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition (2024.naacl-long)

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Challenge: Recent advances in large language models (LLMs) have shown promise in multi-step reasoning tasks, yet relying on extensive manual labeling to provide procedural feedback remains a significant impediment.
Approach: They propose a self-supervised framework that decomposes complex problems into manageable subquestions with a controllable granularity switch and sequentially applies reinforcement learning to iteratively improve the subquest solver.
Outcome: The proposed framework improves performance on mathematical and commonsense reasoning tasks over SOTA.
DGLF: A Dual Graph-based Learning Framework for Multi-modal Sarcasm Detection (2024.emnlp-main)

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Challenge: Existing methods for multimodal sarcasm detection neglect high-order relationships and underestimate high-frequency messages.
Approach: They propose a Dual Graph-based Learning Framework to capture inter-modal inconsistencies . they propose combining a hypergraph and a vanilla graph to achieve enhanced propagation .
Outcome: The proposed model outperforms existing state-of-the-art methods on two benchmark datasets.

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