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Showing 51–100 of 124 papers

TitleStatusHype
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
Improving Unsupervised Question Answering via Summarization-Informed Question Generation—0
Integrated Triaging for Fast Reading Comprehension—0
Keyword-based Query Comprehending via Multiple Optimized-Demand Augmentation—0
Machine Reading Comprehension with Enhanced Linguistic Verifiers—0
MEMEN: Multi-layer Embedding with Memory Networks for Machine Comprehension—0
MemoReader: Large-Scale Reading Comprehension through Neural Memory Controller—0
Mitigating LLM Hallucinations via Conformal Abstention—0
Multi-Mention Learning for Reading Comprehension with Neural Cascades—0
Noisy Pair Corrector for Dense Retrieval—0
On the Influence of Masking Policies in Intermediate Pre-training—0
Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model—0
Quick Dense Retrievers Consume KALE: Post Training Kullback Leibler Alignment of Embeddings for Asymmetrical dual encoders—0
Ranking and Sampling in Open-Domain Question Answering—0
RECONSIDER: Improved Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering—0
Relation-Guided Pre-Training for Open-Domain Question Answering—0
Researchy Questions: A Dataset of Multi-Perspective, Decompositional Questions for LLM Web Agents—0
Rethinking Data Synthesis: A Teacher Model Training Recipe with Interpretation—0
Self-Training Large Language Models for Tool-Use Without Demonstrations—0
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
Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity—0
LACIE: Listener-Aware Finetuning for Confidence Calibration in Large Language ModelsCode0
KV Prediction for Improved Time to First TokenCode0
RE-RAG: Improving Open-Domain QA Performance and Interpretability with Relevance Estimator in Retrieval-Augmented GenerationCode0
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human FeedbackCode0
Judging the Judges: Evaluating Alignment and Vulnerabilities in LLMs-as-JudgesCode0
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