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Reranking

Papers

Showing 226250 of 586 papers

TitleStatusHype
Cross-genre Document Retrieval: Matching between Conversational and Formal Writings0
Hypencoder: Hypernetworks for Information Retrieval0
Creating Causal Embeddings for Question Answering with Minimal Supervision0
How Relevance Emerges: Interpreting LoRA Fine-Tuning in Reranking LLMs0
How Does BERT Rerank Passages? An Attribution Analysis with Information Bottlenecks0
Coupled Representation Learning for Domains, Intents and Slots in Spoken Language Understanding0
A Thorough Comparison of Cross-Encoders and LLMs for Reranking SPLADE0
A Multi-Stage Framework with Taxonomy-Guided Reasoning for Occupation Classification Using Large Language Models0
Higher-order Lexical Semantic Models for Non-factoid Answer Reranking0
Gumbel Reranking: Differentiable End-to-End Reranker Optimization0
Convolutional Neural Networks vs. Convolution Kernels: Feature Engineering for Answer Sentence Reranking0
GTCOM Neural Machine Translation Systems for WMT190
Grounded and Transparent Response Generation for Conversational Information-Seeking Systems0
Conversational Text-to-SQL: An Odyssey into State-of-the-Art and Challenges Ahead0
A Study of Latent Structured Prediction Approaches to Passage Reranking0
A Method of Query Graph Reranking for Knowledge Base Question Answering0
How to Surprisingly Consider Recommendations? A Knowledge-Graph-based Approach Relying on Complex Network Metrics0
GRN: Generative Rerank Network for Context-wise Recommendation0
Graph Exploration Matters: Improving both individual-level and system-level diversity in WeChat Feed Recommender0
GQE-PRF: Generative Query Expansion with Pseudo-Relevance Feedback0
HYRR: Hybrid Infused Reranking for Passage Retrieval0
Continuous Active Learning Using Pretrained Transformers0
If You Can't Beat Them Join Them: Handcrafted Features Complement Neural Nets for Non-Factoid Answer Reranking0
If You Want to Go Far Go Together: Unsupervised Joint Candidate Evidence Retrieval for Multi-hop Question Answering0
Context-Aware Text Normalisation for Historical Dialects0
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