Papers by Shyamal Buch
Neural Event Semantics for Grounded Language Understanding (2021.tacl-1)
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| Challenge: | a new framework for compositional grounded language understanding is proposed . NES is trainable end-to-end by gradient descent with minimal supervision. |
| Approach: | They propose a conjunctivist framework for compositional grounded language understanding . they use words as classifiers that compose to form a sentence meaning by multiplying output scores . |
| Outcome: | The proposed framework improves on compositional grounded language tasks. |
OVFact: Measuring and Improving Open-Vocabulary Factuality for Long Caption Models (2025.findings-emnlp)
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| Challenge: | Large vision-language models struggle to generate long and factual captions . traditional measures for hallucination and factuality are not well suited for longer captions. |
| Approach: | They propose a method for measuring caption factuality of long captions that leverages open-vocabulary visual grounding and tool-based verification without relying on human annotations. |
| Outcome: | The proposed method improves agreement with human judgements and captures both caption descriptiveness and factual precision in the same metric. |