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  • 2024.1: We propose a new instruction tuning dataset (INTERS) for unlocking the power of LLMs on search tasks. See more details.
  • 2023.11: We analyze the risk of data leakage in LLM pre-training and write a new paper to alert this problem. See more details.
  • 2023.8: We write a new survey about applying large language models for information retrieval. See more details.
  • 2023.8: We publish a new version of YuLan-Chat. It achieves better performance than the official LLaMA-2 and LLaMA-2-Chat on MMLU, C-Eval, and AGI-Gaokao benchmarks! GitHub Repo stars

Yutao ZHU's Projects

coca icon coca

CIKM 2021: Contrastive Learning of User Behavior Sequence for Context-Aware Document Ranking

csn icon csn

ECIR 2021: Content Selection Network for Document-grounded Retrieval-based Chatbots

daod.github.io icon daod.github.io

AcadHomepage: A Modern and Responsive Academic Personal Homepage

dcl icon dcl

From Easy to Hard: A Dual Curriculum Learning Framework for Context-Aware Document Ranking

inters icon inters

This is the repository for our paper "INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuning"

kpn icon kpn

SIGIR 2021: Proactive Retrieval-based Chatbots based on Relevant Knowledge and Goals

nmt icon nmt

TensorFlow Neural Machine Translation Tutorial

parlai icon parlai

A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

reboost icon reboost

IR Journal 2019: ReBoost: A Retrieval-Boosted Sequence-to-Sequence Model for Neural Response Generation

scriptwriter icon scriptwriter

ACL 2020: ScriptWriter: Narrative-Guided Script Generation

tensorflow icon tensorflow

Computation using data flow graphs for scalable machine learning

thpp icon thpp

TH++, C++ interface to the torch7 TH library

transformers_cl icon transformers_cl

Source code for the paper "Curriculum Learning Strategies for IR: An Empirical Study on Conversation Response Ranking" at ECIR'20

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