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Passage Ranking
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Chain-of-Thought Poisoning Attacks against R1-based Retrieval-Augmented Generation Systems
Passage Query Methods for Retrieval and Reranking in Conversational Agents
Sliding Windows Are Not the End: Exploring Full Ranking with Long-Context Large Language Models
CURE: A dataset for Clinical Understanding & Retrieval Evaluation
IRLab@iKAT24: Learned Sparse Retrieval with Multi-aspect LLM Query Generation for Conversational Search
RRADistill: Distilling LLMs' Passage Ranking Ability for Long-Tail Queries Document Re-Ranking on a Search Engine
Mamba Retriever: Utilizing Mamba for Effective and Efficient Dense Retrieval
Re-Ranking Step by Step: Investigating Pre-Filtering for Re-Ranking with Large Language Models
DemoRank: Selecting Effective Demonstrations for Large Language Models in Ranking Task
Leveraging Passage Embeddings for Efficient Listwise Reranking with Large Language Models
Approximate Cluster-Based Sparse Document Retrieval with Segmented Maximum Term Weights
GenQREnsemble: Zero-Shot LLM Ensemble Prompting for Generative Query Reformulation
The Surprising Effectiveness of Rankers Trained on Expanded Queries
Shallow Cross-Encoders for Low-Latency Retrieval
Measuring Bias in a Ranked List using Term-based Representations
Searching Dense Representations with Inverted Indexes
PaRaDe: Passage Ranking using Demonstrations with Large Language Models
Context Aware Query Rewriting for Text Rankers using LLM
Vector Search with OpenAI Embeddings: Lucene Is All You Need
Hybrid Retrieval and Multi-stage Text Ranking Solution at TREC 2022 Deep Learning Track
Learning to Rank in Generative Retrieval
GripRank: Bridging the Gap between Retrieval and Generation via the Generative Knowledge Improved Passage Ranking
Fusion-in-T5: Unifying Document Ranking Signals for Improved Information Retrieval
How Does Generative Retrieval Scale to Millions of Passages?
Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents
T2Ranking: A large-scale Chinese Benchmark for Passage Ranking
LEAD: Liberal Feature-based Distillation for Dense Retrieval
On the Impact of Speech Recognition Errors in Passage Retrieval for Spoken Question Answering
Order-Disorder: Imitation Adversarial Attacks for Black-box Neural Ranking Models
Adaptive Re-Ranking with a Corpus Graph
Sparse Pairwise Re-ranking with Pre-trained Transformers
PReGAN: Answer Oriented Passage Ranking with Weakly Supervised GAN
HLATR: Enhance Multi-stage Text Retrieval with Hybrid List Aware Transformer Reranking
Analysing the Robustness of Dual Encoders for Dense Retrieval Against Misspellings
Text and Code Embeddings by Contrastive Pre-Training
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.