TriviaQA
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Benchmarks
BIG-bench
Most implemented
Longformer: The Long-Document Transformer
Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
Relevance-guided Supervision for OpenQA with ColBERT
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Papers
Retrieval-Augmented Generation as Noisy In-Context Learning: A Unified Theory and Risk Bounds
Retrieval-augmented generation (RAG) has seen many empirical successes in recent years by aiding the LLM with external knowledge. However, its theoretical aspect has remained mostly unexplored. In this paper, we propose …
In-Context LearningNatural QuestionsRAGRetrieval+2GenKI: Enhancing Open-Domain Question Answering with Knowledge Integration and Controllable Generation in Large Language Models
Open-domain question answering (OpenQA) represents a cornerstone in natural language processing (NLP), primarily focused on extracting answers from unstructured textual data. With the rapid advancements in Large Language…
Open-Domain Question AnsweringPassage RetrievalQuestion AnsweringRetrieval+1HASH-RAG: Bridging Deep Hashing with Retriever for Efficient, Fine Retrieval and Augmented Generation
Retrieval-Augmented Generation (RAG) encounters efficiency challenges when scaling to massive knowledge bases while preserving contextual relevance. We propose Hash-RAG, a framework that integrates deep hashing technique…
ChunkingDeep HashingPrompt EngineeringRAG+3Semantic Caching of Contextual Summaries for Efficient Question-Answering with Language Models
Large Language Models (LLMs) are increasingly deployed across edge and cloud platforms for real-time question-answering and retrieval-augmented generation. However, processing lengthy contexts in distributed systems incu…
Question AnsweringRetrievalRetrieval-augmented GenerationTriviaQADYNAMAX: Dynamic computing for Transformers and Mamba based architectures
Early exits (EEs) offer a promising approach to reducing computational costs and latency by dynamically terminating inference once a satisfactory prediction confidence on a data sample is achieved. Although many works in…
MambaTriviaQATruthfulQAShED-HD: A Shannon Entropy Distribution Framework for Lightweight Hallucination Detection on Edge Devices
Large Language Models (LLMs) have demonstrated impressive capabilities on a broad array of NLP tasks, but their tendency to produce hallucinations$\unicode{x2013}$plausible-sounding but factually incorrect content$\unico…
HallucinationTriviaQA