Aug 2026· Annual Meeting of the Association for Computational Linguistics· pp. 31109-31124· 0 citations· 21 references
Computer Science
Abstract
Indirect speech acts (ISAs) require pragmatic reasoning over context, as directive intent can- not be inferred from surface form alone. Prior text-based studies and existing multimodal benchmarks largely overlook this requirement, focusing instead on explicitly encoded context or perceptual recognition, and thus underex- plore context-dependent pragmatic understand- ing, particularly in high-context languages such as Korean. We introduce READI, a multimodal benchmark for evaluating ISA understanding through integrated reasoning over visual con- text and dialogue. READI models graded in- directness grounded in pragmatic theory and formulates the task as vision-based pragmatic question answering (V-PQA), supporting cross- lingual evaluation in English and Korean. Ex- periments show that even state-of-the-art multi- modal models struggle with visually grounded indirect speech acts, with performance declin- ing as indirectness increases, underscoring the need for benchmarks that explicitly target con- textual pragmatic reasoning.
A scalable framework that identifies text-biased surface interpretations and converts disagreement regions into conflict QA examples and develops an agentic-style reasoning framework that converts speech into an Audio Twin, a text-readable representation of localized acoustic cues that exposes acoustic evidence to the...
Yen-Ju Lu, Yu-Zhe Wang, Yao-Han Guan et al.· 1 citation
The results show that gesture alone is predictive of the intended referent and that multimodal fusion is most beneficial when the transcript-based model is uncertain, and that training-only alignment of learned representations with the referent image further improves the fusion model performance.
E. Ghaleb, Hugh Mee Wong, Kristina Kobrock· 1 citation
A benchmark for evaluating whether models can infer the implicit, non-linear, and rhetorically layered meanings of social media videos that appear nonsensical on the surface but convey deliberate pragmatic meanings, and a diagnostic setting for measuring the gap between multimodal perception and pragmatic comprehension...
Yang Wang, Ya-Nan Ma, Yiqi Liu et al.· 0 citations
The proposed Multi-turn Multimodal Interactive Dialogue (MMID) Benchmark enables comprehensive evaluation of the Perception, Memorization, and Reasoning abilities of MLLMs, and reveals MLLMs perform well with text-based input but degrade with images, requiring improved leverage fine-grained visual cues.
Seulgi Kim, Juoh Sun, Sumin Kim et al.· Proceedings of the 32nd ACM...· 0 citations
Multimodal foundation models are increasingly used in speech-first assistants that must interpret spoken queries and produce visually grounded decisions. Yet it remains unclear whether semantically equivalent queries yield consistent judgments across modality (text vs. speech) and language (English vs. Arabic). We intr...
Basel Mousi, Fahim Dalvi, S. Chowdhury et al.· 2 citations
This work introduces TAKE 85, the first benchmark for directorial-intent understanding, comprising 398 short films with expert-verified question-answer pairs spanning global and fine-grained visual and audio intent, and establishes directorial intent as a previously overlooked dimension of multimodal understanding.
Kaishuu Shinozaki-Conefrey, Olivier Pascaud, Robin Courant et al.· 0 citations
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