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TriviaQA

Papers

Showing 2650 of 124 papers

TitleStatusHype
Generation-Augmented Retrieval for Open-domain Question AnsweringCode1
Leveraging Passage Retrieval with Generative Models for Open Domain Question AnsweringCode1
Recurrent Chunking Mechanisms for Long-Text Machine Reading ComprehensionCode1
Knowledge Guided Text Retrieval and Reading for Open Domain Question AnsweringCode1
Simple and Effective Multi-Paragraph Reading ComprehensionCode1
TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading ComprehensionCode1
Retrieval-Augmented Generation as Noisy In-Context Learning: A Unified Theory and Risk Bounds0
GenKI: Enhancing Open-Domain Question Answering with Knowledge Integration and Controllable Generation in Large Language ModelsCode0
HASH-RAG: Bridging Deep Hashing with Retriever for Efficient, Fine Retrieval and Augmented Generation0
Semantic Caching of Contextual Summaries for Efficient Question-Answering with Language Models0
DYNAMAX: Dynamic computing for Transformers and Mamba based architectures0
ShED-HD: A Shannon Entropy Distribution Framework for Lightweight Hallucination Detection on Edge Devices0
CacheFocus: Dynamic Cache Re-Positioning for Efficient Retrieval-Augmented Generation0
Cost-Saving LLM Cascades with Early Abstention0
Self-Training Large Language Models for Tool-Use Without Demonstrations0
Vision-centric Token Compression in Large Language Model0
ASRank: Zero-Shot Re-Ranking with Answer Scent for Document Retrieval0
Improving Generated and Retrieved Knowledge Combination Through Zero-shot Generation0
DragonVerseQA: Open-Domain Long-Form Context-Aware Question-AnsweringCode0
Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity0
Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI0
Rethinking Data Synthesis: A Teacher Model Training Recipe with Interpretation0
KV Prediction for Improved Time to First TokenCode0
SFR-RAG: Towards Contextually Faithful LLMs0
Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting0
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