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Showing 51–100 of 124 papers

TitleStatusHype
What's in a Name? Answer Equivalence For Open-Domain Question AnsweringCode0
Episodic Memory Reader: Learning What to Remember for Question Answering from Streaming DataCode0
A Discrete Hard EM Approach for Weakly Supervised Question AnsweringCode0
Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading ComprehensionCode0
RFiD: Towards Rational Fusion-in-Decoder for Open-Domain Question AnsweringCode0
SFR-RAG: Towards Contextually Faithful LLMs—0
ShED-HD: A Shannon Entropy Distribution Framework for Lightweight Hallucination Detection on Edge Devices—0
Simple and Effective Semi-Supervised Question Answering—0
SKILL: Structured Knowledge Infusion for Large Language Models—0
Smarnet: Teaching Machines to Read and Comprehend Like Human—0
Sorted LLaMA: Unlocking the Potential of Intermediate Layers of Large Language Models for Dynamic Inference—0
Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting—0
Studying Strategically: Learning to Mask for Closed-book QA—0
The Generative AI Paradox on Evaluation: What It Can Solve, It May Not Evaluate—0
Tradeoffs in Sentence Selection Techniques for Open-Domain Question Answering—0
UnitedQA: A Hybrid Approach for Open Domain Question Answering—0
Vision-centric Token Compression in Large Language Model—0
When to Read Documents or QA History: On Unified and Selective Open-domain QA—0
Semantic Caching of Contextual Summaries for Efficient Question-Answering with Language Models—0
You Only Need One Model for Open-domain Question Answering—0
Retrieval-Augmented Generation as Noisy In-Context Learning: A Unified Theory and Risk Bounds—0
A Copy-Augmented Generative Model for Open-Domain Question Answering—0
A Copy-Augmented Generative Model for Open-Domain Question Answering—0
Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI—0
A Deep Cascade Model for Multi-Document Reading Comprehension—0
Adversarial Retriever-Ranker for dense text retrieval—0
A Multi-Stage Memory Augmented Neural Network for Machine Reading Comprehension—0
ASRank: Zero-Shot Re-Ranking with Answer Scent for Document Retrieval—0
Attendre: Wait To Attend By Retrieval With Evicted Queries in Memory-Based Transformers for Long Context Processing—0
Attention-guided Generative Models for Extractive Question Answering—0
Allies: Prompting Large Language Model with Beam Search—0
CacheFocus: Dynamic Cache Re-Positioning for Efficient Retrieval-Augmented Generation—0
Can Open-Domain QA Reader Utilize External Knowledge Efficiently like Humans?—0
Challenges in Generalization in Open Domain Question Answering—0
CLAM: Selective Clarification for Ambiguous Questions with Generative Language Models—0
Contextualized Representations Using Textual Encyclopedic Knowledge—0
Cost-Saving LLM Cascades with Early Abstention—0
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing—0
Deep Understanding based Multi-Document Machine Reading Comprehension—0
Dense Sparse Retrieval: Using Sparse Language Models for Inference Efficient Dense Retrieval—0
DYNAMAX: Dynamic computing for Transformers and Mamba based architectures—0
Efficient Transformer Knowledge Distillation: A Performance Review—0
Evaluating Neural Model Robustness for Machine Comprehension—0
FiE: Building a Global Probability Space by Leveraging Early Fusion in Encoder for Open-Domain Question Answering—0
Fine-Grained Self-Endorsement Improves Factuality and Reasoning—0
FIT-RAG: Black-Box RAG with Factual Information and Token Reduction—0
GNN-encoder: Learning a Dual-encoder Architecture via Graph Neural Networks for Dense Passage Retrieval—0
Grow-and-Clip: Informative-yet-Concise Evidence Distillation for Answer Explanation—0
HASH-RAG: Bridging Deep Hashing with Retriever for Efficient, Fine Retrieval and Augmented Generation—0
Improving Generated and Retrieved Knowledge Combination Through Zero-shot Generation—0
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