Papers by Sunny Manchanda
GRAFT: A Graph-based Flow-aware Agentic Framework for Document-level Machine Translation (2025.emnlp-industry)
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| Challenge: | Existing Document-level machine translation systems struggle to handle discourse-level phenomena such as pronoun resolution, lexical cohesion, and ellipsis. |
| Approach: | They propose a graph-based document-level machine translation framework that leverages Large Language Models to model translation flow and discourse structure. |
| Outcome: | The proposed framework outperforms commercial and closed systems in eight languages and six domains. |
Small Language Models Fine-tuned to Coordinate Larger Language Models improve Complex Reasoning (2023.emnlp-main)
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| Challenge: | Recent attempts at prompt decomposition toward solving complex, multi-step reasoning problems depend on the ability of the LLM to simultaneously decompose and solve the problem. |
| Approach: | They propose a decomposition generator that decomposes complex problems into subproblems that require fewer reasoning steps. |
| Outcome: | The proposed method can produce competitive or even better performance compared to its larger successor, GPT-4. |