Papers by Ashutosh Sharma
IndicIRSuite: Multilingual Dataset and Neural Information Models for Indian Languages (2024.acl-short)
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| Challenge: | IndicIRSuite is the first attempt at building large-scale Neural Information Retrieval resources for a large number of Indian languages. |
| Approach: | They introduce Neural Information Retrieval resources for 11 widely spoken Indian Languages from two major Indian language families. |
| Outcome: | Experiments show that Indic-ColBERT improves on INDIC-MARCO datasets for 11 languages, and that it can be used to improve IR for Indian languages. |
IL-TUR: Benchmark for Indian Legal Text Understanding and Reasoning (2024.acl-long)
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| Challenge: | Legal systems worldwide struggle with exponentially growing legal cases in various courts. |
| Approach: | They propose a benchmark for Indian legal text understanding and reasoning task that includes domain-specific tasks that address different aspects of the legal system. |
| Outcome: | The proposed benchmark for Indian legal text understanding and reasoning aims to address the gap between models and the ground truth. |
CheckersGPT: Learning World Models through Language Modeling (2024.acl-srw)
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| Challenge: | Large Language Models (LLMs) have shown impressive performance on various tasks, but the underlying process behind predicting the desired next token remains a black box. |
| Approach: | They train a GPT-style autoregressive language model using only the next character prediction objective and then train corresponding model with different layer sizes. |
| Outcome: | The proposed model shows a hint of learning a world model representation of the board positions on a simulated game of checkers and human gameplay dataset. |
PoseStitch-SLT: Linguistically Inspired Pose-Stitching for End-to-End Sign Language Translation (2025.emnlp-main)
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| Challenge: | Sign language translation remains a challenging task due to the scarcity of large-scale, sentence-aligned datasets. |
| Approach: | They propose a pose-based pre-training scheme that is inspired by a linguistic-templates-based sentence generation technique. |
| Outcome: | The proposed pre-training scheme outperforms state-of-the-art methods for pose-based gloss-free translation on two sign language datasets. |
U-CREAT: Unsupervised Case Retrieval using Events extrAcTion (2023.acl-long)
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| Challenge: | Prior Case Retrieval (PCR) is about automatically citing relevant prior legal cases in a given query case. |
| Approach: | They propose a new benchmark for prior case retrieval based on a legal query case . they propose an unsupervised retrieval method-based pipeline U-CREAT . |
| Outcome: | The proposed method significantly improves performance and makes retrieval faster compared to BM25. |
Angel: Enterprise Search System for the Non-Profit Industry (2023.emnlp-industry)
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| Challenge: | Non-profit industry needs a system for accurately matching fund-seekers with fund-givers aligned in cause and target beneficiary group. |
| Approach: | They propose a search system that takes a fund-giver’s mission description as input and returns a ranked list of fund-seekers as output. |
| Outcome: | The proposed system improves on the non-profit evaluation dataset and the state-of-the-art model. |