The official implementation of ICLR 2020, "Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering".
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Updated
Jul 25, 2024 - Python
The official implementation of ICLR 2020, "Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering".
Codes for NAACL 2021 Paper "Unsupervised Multi-hop Question Answering by Question Generation"
Implementation of Not All Contexts Are Equal: Teaching LLMs Credibility-aware Generation. Paper: https://arxiv.org/abs/2404.06809
Pytorch implementation of "A Simple Yet Strong Pipeline for HotpotQA" (Groeneveld, D., Khot, T., & Sabharwal, A.). Now developing!
Enhancing Retrieval-Augmented Generation with Document Link Structure for Multi-hop Web Question Answering
This codebase implements a Retrieval-Augmented Generation (RAG) chatbot using the Gemini API and DSPy framework, designed to answer questions based on the HotPotQA dataset. It includes components for loading data, generating responses, and evaluating model performance through various QA strategies, including basic QA and multi-hop retrieval.
Exploration of retrieval methods on the HotpotQA corpus, combining dense retrieval and feature-based reranking. Achieved a mean nDCG@10 of 0.9416 using LambdaRank with features such as cross-encoder score, LLM score, BM25 score, and token-based statistics—surpassing dense retriever + cross-encoder baselines.
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