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Diganta Misra

7 accepted papers

2025

(Almost) Free Modality Stitching of Foundation Models

EMNLP 2025

Foundation multi-modal models are often designed by stitching of multiple existing pretrained uni-modal models: for example, an image classifier with a text model. This stitching process is performed by training a connector module that aims to align the representation spaces of these uni-modal model

2025

Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code

COLING 2025industry

Pretrained language models are integral part of AI applications, but their high computational cost for training limits accessibility. Initiatives such as Bloom and StarCoder aim to democratize access to pretrained models for collaborative community development. Despite these efforts, such models enc…

Cited by 2SourcePDFScholar
2025

Bridging the Data Provenance Gap Across Text, Speech, and Video

ICLR 2025poster

Progress in AI is driven largely by the scale and quality of training data. Despite this, there is a deficit of empirical analysis examining the attributes of well-established datasets beyond text. In this work we conduct the largest and first-of-its-kind longitudinal audit across modalities --- pop…

Cited by 1SourcePDFScholar
2025

MMTEB: Massive Multilingual Text Embedding Benchmark

ICLR 2025poster

Text embeddings are typically evaluated on a narrow set of tasks, limited in terms of languages, domains, and task types. To circumvent this limitation and to provide a more comprehensive evaluation, we introduce the Massive Multilingual Text Embedding Benchmark (MMTEB) -- a large-scale community-dr…

2025

Using Shapley interactions to understand how models use structure

ACL 2025long

Language is an intricately structured system, and a key goal of NLP interpretability is to provide methodological insights for understanding how language models internally represent this structure. In this paper, we use Shapley Taylor interaction indices (STII) in order to examine how language and s…

Cited by 0SourcePDFScholar
2024

Consent in Crisis: The Rapid Decline of the AI Data Commons

NeurIPS 2024poster

General-purpose artificial intelligence (AI) systems are built on massive swathes of public web data, assembled into corpora such as C4, RefinedWeb, and Dolma. To our knowledge, we conduct the first, large-scale, longitudinal audit of the consent protocols for the web domains underlying AI training…

Cited by 36SourceScholar
2024

Slight Corruption in Pre-training Data Makes Better Diffusion Models

NeurIPS 2024spotlight

Diffusion models (DMs) have shown remarkable capabilities in generating realistic high-quality images, audios, and videos. They benefit significantly from extensive pre-training on large-scale datasets, including web-crawled data with paired data and conditions, such as image-text and image-class p…

Cited by 6SourcePDFScholar