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

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Showing 4151–4175 of 10817 papers

TitleStatusHype
DLS@CU at SemEval-2016 Task 1: Supervised Models of Sentence Similarity—0
BERT for Question Generation—0
A Factoid Question Answering System Using Answer Pattern Matching—0
HOP, UNION, GENERATE: Explainable Multi-hop Reasoning without Rationale Supervision—0
BERTERS: Multimodal Representation Learning for Expert Recommendation System with Transformer—0
DLIP: Distilling Language-Image Pre-training—0
3D-MoE: A Mixture-of-Experts Multi-modal LLM for 3D Vision and Pose Diffusion via Rectified Flow—0
BERT-CoQAC: BERT-based Conversational Question Answering in Context—0
DKPro Keyphrases: Flexible and Reusable Keyphrase Extraction Experiments—0
An Introduction to Natural Language Processing Techniques and Framework for Clinical Implementation in Radiation Oncology—0
HOLMES: Hyper-Relational Knowledge Graphs for Multi-hop Question Answering using LLMs—0
DIVKNOWQA: Assessing the Reasoning Ability of LLMs via Open-Domain Question Answering over Knowledge Base and Text—0
Divide & Conquer for Entailment-aware Multi-hop Evidence Retrieval—0
A Factoid Question Answering System for Vietnamese—0
Divide and Conquer: Text Semantic Matching with Disentangled Keywords and Intents—0
BERT Based Clinical Knowledge Extraction for Biomedical Knowledge Graph Construction and Analysis—0
A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions—0
Honest Students from Untrusted Teachers: Learning an Interpretable Question-Answering Pipeline from a Pretrained Language Model—0
How Does BERT Answer Questions? A Layer-Wise Analysis of Transformer Representations—0
An Interactive Web-Interface for Visualizing the Inner Workings of the Question Answering LSTM—0
Diversity Enhances an LLM's Performance in RAG and Long-context Task—0
BenLLMEval: A Comprehensive Evaluation into the Potentials and Pitfalls of Large Language Models on Bengali NLP—0
Diversity and Consistency: Exploring Visual Question-Answer Pair Generation—0
3DLLM-Mem: Long-Term Spatial-Temporal Memory for Embodied 3D Large Language Model—0
Diversify-verify-adapt: Efficient and Robust Retrieval-Augmented Ambiguous Question Answering—0
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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