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 8251–8300 of 10817 papers

TitleStatusHype
Inference to the Best Explanation in Large Language Models—0
Inference Scaled GraphRAG: Improving Multi Hop Question Answering on Knowledge Graphs—0
A Two-Stage Approach towards Generalization in Knowledge Base Question Answering—0
In Factuality: Efficient Integration of Relevant Facts for Visual Question Answering—0
CREPE: Coordinate-Aware End-to-End Document Parser—0
A Two Level Model for Context Sensitive Inference Rules—0
An Analysis of Causality between Events and its Relation to Temporal Information—0
Inducing Script Structure from Crowdsourced Event Descriptions via Semi-Supervised Clustering—0
Inducing Neural Models of Script Knowledge—0
Inducing Latent Semantic Relations for Structured Distributional Semantics—0
Inducing Example-based Semantic Frames from a Massive Amount of Verb Uses—0
Creation of Corpus and Analysis in Code-Mixed Kannada-English Social Media Data for POS Tagging—0
In-domain Context-aware Token Embeddings Improve Biomedical Named Entity Recognition—0
Creation and use of Language Resources in a Question-Answering eHealth System—0
Attribute Value Generation from Product Title using Language Models—0
A Named Entity Recognition Shootout for German—0
A Discriminative Semantic Ranker for Question Retrieval—0
INDIC QA BENCHMARK: A Multilingual Benchmark to Evaluate Question Answering capability of LLMs for Indic Languages—0
Creating Causal Embeddings for Question Answering with Minimal Supervision—0
Creating Arabic LLM Prompts at Scale—0
Incremental Tree Substitution Grammar for Parsing and Sentence Prediction—0
Incremental Reading for Question Answering—0
Creating a PurposeNet Ontology: An insight into the issues encountered during ontology creation—0
Incremental Knowledge Based Question Answering—0
Incremental Improvement of a Question Answering System by Re-ranking Answer Candidates using Machine Learning—0
Creating and using large monolingual parallel corpora for sentential paraphrase generation—0
Analyzing Zero-Shot Abilities of Vision-Language Models on Video Understanding Tasks—0
Incremental Comprehension of Garden-Path Sentences by Large Language Models: Semantic Interpretation, Syntactic Re-Analysis, and Attention—0
Increasing the LLM Accuracy for Question Answering: Ontologies to the Rescue!—0
Increasing the Difficulty of Automatically Generated Questions via Reinforcement Learning with Synthetic Preference—0
Incorporating Trustiness and Collective Synonym/Contrastive Evidence into Taxonomy Construction—0
Incorporating Selectional Preferences in Multi-hop Relation Extraction—0
A Discriminative Hierarchical Model for Fast Coreference at Large Scale—0
A Cheap Linear Attention Mechanism with Fast Lookups and Fixed-Size Representations—0
Incorporating Question Answering-Based Signals into Abstractive Summarization via Salient Span Selection—0
Incorporating medical knowledge in BERT for clinical relation extraction—0
CRAFT: Training-Free Cascaded Retrieval for Tabular QA—0
Incorporating External Knowledge to Answer Open-Domain Visual Questions with Dynamic Memory Networks—0
Incorporating External Knowledge into Machine Reading for Generative Question Answering—0
Incorporating Contextual and Syntactic Structures Improves Semantic Similarity Modeling—0
CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractions—0
In-Context Learning with Topological Information for Knowledge Graph Completion—0
CQ-VQA: Visual Question Answering on Categorized Questions—0
In-Context Learning for Knowledge Base Question Answering for Unmanned Systems based on Large Language Models—0
In-Context Ability Transfer for Question Decomposition in Complex QA—0
In ChatGPT We Trust? Measuring and Characterizing the Reliability of ChatGPT—0
CQARE: Contrastive Question-Answering for Few-shot Relation Extraction with Prompt Tuning—0
Attentive Recurrent Tensor Model for Community Question Answering—0
Analyzing the Efficacy of an LLM-Only Approach for Image-based Document Question Answering—0
InCA: Rethinking In-Car Conversational System Assessment Leveraging Large Language Models—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