SOTAVerified

Question Answering

Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.

( Image credit: SQuAD )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4401–4450 of 10817 papers

TitleStatusHype
FINECAPTION: Compositional Image Captioning Focusing on Wherever You Want at Any Granularity—0
Find the word that does not belong: A Framework for an Intrinsic Evaluation of Word Vector Representations—0
CLAMP: Contrastive LAnguage Model Prompt-tuning—0
ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings—0
Aligning MAGMA by Few-Shot Learning and Finetuning—0
Find The Gap: Knowledge Base Reasoning For Visual Question Answering—0
Finding What Matters in Questions—0
Finding the Middle Ground - A Model for Planning Satisficing Answers—0
Finding the Evidence: Localization-aware Answer Prediction for Text Visual Question Answering—0
City-VLM: Towards Multidomain Perception Scene Understanding via Multimodal Incomplete Learning—0
ARS\_NITK at MEDIQA 2019:Analysing Various Methods for Natural Language Inference, Recognising Question Entailment and Medical Question Answering System—0
Findings on Conversation Disentanglement—0
Findings of the Second BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora—0
Finding Similar Medical Questions from Question Answering Websites—0
Aligning LLMs through Multi-perspective User Preference Ranking-based Feedback for Programming Question Answering—0
Finding ReMO (Related Memory Object): A Simple Neural Architecture for Text based Reasoning—0
Finding Optimal 1-Endpoint-Crossing Trees—0
Citations and Trust in LLM Generated Responses—0
Finding Generalizable Evidence by Learning to Convince Q\&A Models—0
Citation Analysis with Neural Attention Models—0
Finding Answers from the Word of God: Domain Adaptation for Neural Networks in Biblical Question Answering—0
FinDER: Financial Dataset for Question Answering and Evaluating Retrieval-Augmented Generation—0
CinePile: A Long Video Question Answering Dataset and Benchmark—0
Financial Knowledge Large Language Model—0
CIKQA: Learning Commonsense Inference with a Unified Knowledge-in-the-loop QA Paradigm—0
Around the GLOBE: Numerical Aggregation Question-Answering on Heterogeneous Genealogical Knowledge Graphs with Deep Neural Networks—0
Adapting Large Language Models to Domains via Reading Comprehension—0
A Biomedical Question Answering System in BioASQ 2017—0
FilterRAG: Zero-Shot Informed Retrieval-Augmented Generation to Mitigate Hallucinations in VQA—0
CICBUAPnlp: Graph-Based Approach for Answer Selection in Community Question Answering Task—0
CIC: A Framework for Culturally-Aware Image Captioning—0
A Robustly Optimized BERT Pre-training Approach with Post-training—0
Fill-in-the-Blank: A Challenging Video Understanding Evaluation Framework—0
Filling a Knowledge Graph with a Crowd—0
FiE: Building a Global Probability Space by Leveraging Early Fusion in Encoder for Open-Domain Question Answering—0
A Road-map Towards Explainable Question Answering A Solution for Information Pollution—0
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference—0
FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation—0
FiDeLiS: Faithful Reasoning in Large Language Model for Knowledge Graph Question Answering—0
CHOPT : Automated Hyperparameter Optimization Framework for Cloud-Based Machine Learning Platforms—0
FFA Sora, video generation as fundus fluorescein angiography simulator—0
Few-Shot VQA with Frozen LLMs: A Tale of Two Approaches—0
Few-shot Unified Question Answering: Tuning Models or Prompts?—0
Chop Chop BERT: Visual Question Answering by Chopping VisualBERT's Heads—0
Choosing which to use? A study of distributional models for nominal lexical semantic classification—0
Adapting Large Language Models for Multi-Domain Retrieval-Augmented-Generation—0
Few-shot Question Generation for Personalized Feedback in Intelligent Tutoring Systems—0
Few-shot Query-Focused Summarization with Prefix-Merging—0
Choose Your QA Model Wisely: A Systematic Study of Generative and Extractive Readers for Question Answering—0
Few-shot Policy (de)composition in Conversational Question Answering—0
Show:102550
← PrevPage 89 of 217Next →
All datasetsSQuAD2.0SQuAD1.1HotpotQAPIQABoolQCOPATriviaQASQuAD1.1 devNatural QuestionsOpenBookQATruthfulQAMultiRC

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94—Unverified
2FPNet (ensemble)EM90.87—Unverified
3IE-NetV2 (ensemble)EM90.86—Unverified
4SA-Net on Albert (ensemble)EM90.72—Unverified
5SA-Net-V2 (ensemble)EM90.68—Unverified
6FPNet (ensemble)EM90.6—Unverified
7Retro-Reader (ensemble)EM90.58—Unverified
8EntitySpanFocusV2 (ensemble)EM90.52—Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49—Unverified
10EntitySpanFocus+AT (ensemble)EM90.45—Unverified