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 7451–7500 of 10817 papers

TitleStatusHype
POIReviewQA: A Semantically Enriched POI Retrieval and Question Answering Dataset—0
PokemonChat: Auditing ChatGPT for Pokémon Universe Knowledge—0
A Study of Association Measures and their Combination for Arabic MWT Extraction—0
Polaris: A Safety-focused LLM Constellation Architecture for Healthcare—0
Grounded Knowledge-Enhanced Medical VLP for Chest X-Ray—0
Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region—0
Policy Compliance Detection via Expression Tree Inference—0
Policy-Gradient Training of Language Models for Ranking—0
Compressing Visual-linguistic Model via Knowledge Distillation—0
Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations—0
Extracting Psychological Indicators Using Question Answering—0
POLYGLOT: Multilingual Semantic Role Labeling with Unified Labels—0
Compressing Long Context for Enhancing RAG with AMR-based Concept Distillation—0
A Study into Investigating Temporal Robustness of LLMs—0
PolyLM: An Open Source Polyglot Large Language Model—0
POLY: Mining Relational Paraphrases from Multilingual Sentences—0
PolySmart @ TRECVid 2024 Medical Video Question Answering—0
PolyUCOMP: Combining Semantic Vectors with Skip bigrams for Semantic Textual Similarity—0
A Model of Vietnamese Person Named Entity Question Answering System—0
Extracting Training Data from Document-Based VQA Models—0
Accelerating Large Language Model Pretraining via LFR Pedagogy: Learn, Focus, and Review—0
GripRank: Bridging the Gap between Retrieval and Generation via the Generative Knowledge Improved Passage Ranking—0
Portuguese Named Entity Recognition using Conditional Random Fields and Local Grammars—0
Extraction Meets Abstraction: Ideal Answer Generation for Biomedical Questions—0
GRILL: Grounded Vision-language Pre-training via Aligning Text and Image Regions—0
A Structured Distributional Semantic Model : Integrating Structure with Semantics—0
Amharic Question Answering for Biography, Definition, and Description Questions—0
Post-training an LLM for RAG? Train on Self-Generated Demonstrations—0
GRILLBot: A multi-modal conversational agent for complex real-world tasks—0
Griffon-G: Bridging Vision-Language and Vision-Centric Tasks via Large Multimodal Models—0
Power in Numbers: Robust reading comprehension by finetuning with four adversarial sentences per example—0
Poze: Sports Technique Feedback under Data Constraints—0
Comprehensive Study on German Language Models for Clinical and Biomedical Text Understanding—0
Extractive Question Answering on Queries in Hindi and Tamil—0
ChartCitor: Multi-Agent Framework for Fine-Grained Chart Visual Attribution—0
PQuAD: A Persian Question Answering Dataset—0
Grid Search Hyperparameter Benchmarking of BERT, ALBERT, and LongFormer on DuoRC—0
Grid-LOGAT: Grid Based Local and Global Area Transcription for Video Question Answering—0
Practical Semantic Parsing for Spoken Language Understanding—0
Practice in Synonym Extraction at Large Scale—0
Extrinsic Evaluation of Machine Translation Metrics—0
PR-Attack: Coordinated Prompt-RAG Attacks on Retrieval-Augmented Generation in Large Language Models via Bilevel Optimization—0
Comprehensive Modeling and Question Answering of Cancer Clinical Practice Guidelines using LLMs—0
A Structured Distributional Semantic Model for Event Co-reference—0
Precise Length Control in Large Language Models—0
Precise Model Benchmarking with Only a Few Observations—0
Precision Empowers, Excess Distracts: Visual Question Answering With Dynamically Infused Knowledge In Language Models—0
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute—0
A dataset of clinically generated visual questions and answers about radiology images—0
Proceedings of the Workshop on Human-Computer 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