Papers by Kashob Kumar Roy
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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Bowen Jin, Chulin Xie, Jiawei Zhang, Kashob Kumar Roy, Yu Zhang, Zheng Li, Ruirui Li, Xianfeng Tang, Suhang Wang, Yu Meng, Jiawei Han
| 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. |