Papers by Rishabh Adiga
Automatic Speech Recognition in Sanskrit: A New Speech Corpus and Modelling Insights (2021.findings-acl)
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| Challenge: | In this paper, we propose the first large scale study of automatic speech recognition in Sanskrit . we focus on the impact of unit selection in San's ASR systems . |
| Approach: | They propose a large scale study of automatic speech recognition in Sanskrit . they propose syllable level unit selection that captures character sequences . |
| Outcome: | The proposed model captures character sequences from one vowel in the word to the next vowela. |
Designing Informative Metrics for Few-Shot Example Selection (2024.findings-acl)
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| Challenge: | Pretrained language models (PLMs) have shown remarkable few-shot learning capabilities when provided with properly formatted examples. |
| Approach: | They propose a complexity-based prompt selection approach for sequence tagging tasks that uses certain metrics to align the syntactico-semantic complexity of test sentences and examples. |
| Outcome: | The proposed approach achieves state-of-the-art performance on few-shot NER, with 5% improvement in F1 score. |
Attention Speaks Volumes: Localizing and Mitigating Bias in Language Models (2025.acl-long)
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| Challenge: | ambiguous comparative prompting frameworks generate biased content when confronted with ambiguously prompts . ambiguity in LLMs can manifest in various forms, including reinforcing stereotypes, displaying gender bias, or demonstrating preferential treatment towards specific demographic groups. |
| Approach: | They propose a technique to localize bias to specific layers of an LLM by analyzing attention scores and then reduce bias by scaling attention in these biased layers. |
| Outcome: | The proposed technique reduces bias by scaling attention in biased layers. |