Papers by Anil Batra

2 papers
CAST: Cross-modal Alignment Similarity Test for Vision Language Models (2025.coling-main)

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Challenge: Vision Language Models (VLMs) are typically evaluated with Visual Question Answering tasks which assess a model’s understanding of scenes.
Approach: They propose to use visual question answering (VQA) to assess a model's understanding of scenes to probe for self-consistency across modalities.
Outcome: The proposed test does not focus on objective accuracy but rather on whether VLMs are internally consistent in their outputs.
Predicting Implicit Arguments in Procedural Video Instructions (2025.acl-long)

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Challenge: Prior SRL benchmarks often miss implicit arguments, leading to incomplete understanding.
Approach: They propose a dataset that necessitates inferring implicit and explicit arguments from contextual information in multimodal cooking procedures.
Outcome: The proposed dataset achieves a 17% relative improvement in F1-score for what-implicit and a 14.7% improvement for where/with-implicative semantic roles over GPT-4o.

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