Papers by Kashob Kumar Roy

2 papers
ConTReGen: Context-driven Tree-structured Retrieval for Open-domain Long-form Text Generation (2024.findings-emnlp)

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Challenge: Existing iterative retrieval-augmented generation approaches struggle to delve deeply into each facet of complex queries.
Approach: They propose a framework that employs a tree-structured retrieval approach to enhance the depth and relevance of retrieved content.
Outcome: The proposed framework outperforms state-of-the-art models on multiple datasets and a newly introduced dataset.
Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs (2024.findings-acl)

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Challenge: Existing studies suggest augmenting LLMs with external text corpora to alleviate hallucination problems.
Approach: They propose to augment large language models with text units retrieved from external knowledge corpora to alleviate the issue.
Outcome: The proposed framework outperforms baselines on GRBench with three LLMs and shows that iterative reasoning outperformed the baselines.

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