https://github.com/lixsh6/tencent_wsdm_cup2023
공식 코드Pretraining De-Biased Language Model with Large-scale Click Logs for Document Ranking
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Ad-hoc information retrieval refers to the task of returning information resources related to a user query formulated in natural language.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Pretraining De-Biased Language Model with Large-scale Click Logs for Document Ranking
Finding the Law: Enhancing Statutory Article Retrieval via Graph Neural Networks
Improving Bi-encoder Document Ranking Models with Two Rankers and Multi-teacher Distillation
BERT Rankers are Brittle: a Study using Adversarial Document Perturbations
LEAD: Liberal Feature-based Distillation for Dense Retrieval
Traditional IR rivals neural models on the MS MARCO Document Ranking Leaderboard
Fusion-in-T5: Unifying Document Ranking Signals for Improved Information Retrieval
Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from LLMs
Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering
Intra-Document Cascading: Learning to Select Passages for Neural Document Ranking
Local Self-Attention over Long Text for Efficient Document Retrieval
Siamese BERT-based Model for Web Search Relevance Ranking Evaluated on a New Czech Dataset
Socialformer: Social Network Inspired Long Document Modeling for Document Ranking
DeepTileBars: Visualizing Term Distribution for Neural Information Retrieval
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
DyVo: Dynamic Vocabularies for Learned Sparse Retrieval with Entities
NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc Information Retrieval
RankMamba: Benchmarking Mamba's Document Ranking Performance in the Era of Transformers
XLNet: Generalized Autoregressive Pretraining for Language Understanding
Simplified TinyBERT: Knowledge Distillation for Document Retrieval
XLNet: Generalized Autoregressive Pretraining for Language Understanding
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.