Papers by Adarsh Kumar
MultiWOZ 2.1: A Consolidated Multi-Domain Dialogue Dataset with State Corrections and State Tracking Baselines (2020.lrec-1)
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Mihail Eric, Rahul Goel, Shachi Paul, Abhishek Sethi, Sanchit Agarwal, Shuyang Gao, Adarsh Kumar, Anuj Goyal, Peter Ku, Dilek Hakkani-Tur
| Challenge: | MultiWOZ 2.0 has substantial noise in dialogue state annotations and dialogue utterances . follow-up work has augmented the original dataset with user dialogue acts . |
| Approach: | They propose to reannotate dialogue state and utterances based on original dataset . they then compare their results to other datasets to improve their models . |
| Outcome: | The proposed dataset improves on the noise in the dialogue state annotations and dialogue utterances. |
SIKeD: Self-guided Iterative Knowledge Distillation for Mathematical Reasoning (2025.findings-acl)
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| Challenge: | Large language models (LLMs) can generate intermediate reasoning process for multistep reasoning tasks. |
| Approach: | They propose a distillation method that teaches the model to approach a task using different strategies and the model uses its self-generated on-policy outputs to choose the most suitable strategy. |
| Outcome: | The proposed method significantly outperforms distillation techniques on large models of different sizes. |
Translating Web Search Queries into Natural Language Questions (L18-1)
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| Challenge: | a new method to generate natural language questions from keyword-based queries is proposed . a synergy between query-to-question problem and standard machine translation (MT) model is found . |
| Approach: | They propose a method to generate well-formed natural language questions from keyword-based queries. |
| Outcome: | The proposed method is well-formed natural language question generated from keyword-based query. |