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Ashish V. Thapliyal

7 accepted papers

2023

Emergence of Abstract State Representations in Embodied Sequence Modeling

EMNLP 2023long main

Decision making via sequence modeling aims to mimic the success of language models, where actions taken by an embodied agent are modeled as tokens to predict. Despite their promising performance, it remains unclear if embodied sequence modeling leads to the emergence of internal representations that…

Cited by 0SourceScholar
2023

MaXM: Towards Multilingual Visual Question Answering

EMNLP 2023long findings

Visual Question Answering (VQA) has been primarily studied through the lens of the English language. Yet, tackling VQA in other languages in the same manner would require a considerable amount of resources. In this paper, we propose scalable solutions to multilingual visual question answering (mVQA)…

Cited by 0SourcecodeScholar
2023

PaLI: A Jointly-Scaled Multilingual Language-Image Model

ICLR 2023top-5%

Effective scaling and a flexible task interface enable large language models to excel at many tasks. We present PaLI, a model that extends this approach to the joint modeling of language and vision. PaLI generates text based on visual and textual inputs, and with this interface performs many vision,…

2022

Crossmodal-3600: A Massively Multilingual Multimodal Evaluation Dataset

EMNLP 2022main

Research in massively multilingual image captioning has been severely hampered by a lack of high-quality evaluation datasets. In this paper we present the Crossmodal-3600 dataset (XM3600 in short), a geographically diverse set of 3600 images annotated with human-generated reference captions in 36 la…

2022

Denoising Large-Scale Image Captioning from Alt-text Data Using Content Selection Models

COLING 2022main

Training large-scale image captioning (IC) models demands access to a rich and diverse set of training examples that are expensive to curate both in terms of time and man-power. Instead, alt-text based captions gathered from the web is a far cheaper alternative to scale with the downside of being no…

Cited by 2SourcePDFScholar
2022

End-to-end Dense Video Captioning as Sequence Generation

COLING 2022main

Dense video captioning aims to identify the events of interest in an input video, and generate descriptive captions for each event. Previous approaches usually follow a two-stage generative process, which first proposes a segment for each event, then renders a caption for each identified segment. Re…

Cited by 50SourcePDFScholar
2021

Quality Estimation for Image Captions Based on Large-scale Human Evaluations

NAACL 2021long

Automatic image captioning has improved significantly over the last few years, but the problem is far from being solved, with state of the art models still often producing low quality captions when used in the wild. In this paper, we focus on the task of Quality Estimation (QE) for image captions, w…