Papers by Shujun Cao

2 papers
Enhancing Attributed Question Answering using Tailored Progressive Curriculum Learning (2025.findings-emnlp)

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Challenge: Attributed Question Answering models are not yet leveraged to enhance their essential capabilities, including evidence identification, cross-source relation recognition and anti-distraction reasoning.
Approach: They propose a progressive progressive curriculum learning approach that optimizes both encoder-decoder and decoder-only AQA models.
Outcome: The proposed approach improves both encoder-decoder and decoder-only AQA models on the quotesum benchmark.
Looking Beyond the One: Operationalizing and Eliciting Visual Ambiguity in VLLMs (2026.acl-long)

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Challenge: Visual question answering systems typically collapse ambiguity, committing to a single interpretation during decoding and evaluation.
Approach: They operationalize ambiguity as the existence of multiple answer-supporting regions in an image . they show that ambiguities are already encoded in their internal representations .
Outcome: The proposed approach makes ambiguity observable without exhaustive annotations . ambiguities are already encoded in models, but not reliably expressed in outputs despite hidden states .

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