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 4251–4275 of 10817 papers

TitleStatusHype
Wav2Prompt: End-to-End Speech Prompt Generation and Tuning For LLM in Zero and Few-shot Learning—0
Are Large Vision Language Models up to the Challenge of Chart Comprehension and Reasoning? An Extensive Investigation into the Capabilities and Limitations of LVLMs—0
SPAGHETTI: Open-Domain Question Answering from Heterogeneous Data Sources with Retrieval and Semantic Parsing—0
Unraveling and Mitigating Retriever Inconsistencies in Retrieval-Augmented Large Language ModelsCode0
Long-Span Question-Answering: Automatic Question Generation and QA-System Ranking via Side-by-Side Evaluation—0
Learning to Clarify: Multi-turn Conversations with Action-Based Contrastive Self-Training—0
Passage-specific Prompt Tuning for Passage Reranking in Question Answering with Large Language ModelsCode0
Video Question Answering for People with Visual Impairments Using an Egocentric 360-Degree Camera—0
Uncovering Bias in Large Vision-Language Models at Scale with Counterfactuals—0
VQA Training Sets are Self-play Environments for Generating Few-shot Pools—0
Evaluating Zero-Shot GPT-4V Performance on 3D Visual Question Answering Benchmarks—0
MetaToken: Detecting Hallucination in Image Descriptions by Meta Classification—0
PathReasoner: Modeling Reasoning Path with Equivalent Extension for Logical Question Answering—0
A Multi-Source Retrieval Question Answering Framework Based on RAG—0
MASSIVE Multilingual Abstract Meaning Representation: A Dataset and Baselines for Hallucination Detection—0
Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study—0
Bridging the Gap: Dynamic Learning Strategies for Improving Multilingual Performance in LLMs—0
RealitySummary: Exploring On-Demand Mixed Reality Text Summarization and Question Answering using Large Language Models—0
Data-augmented phrase-level alignment for mitigating object hallucination—0
ATM: Adversarial Tuning Multi-agent System Makes a Robust Retrieval-Augmented GeneratorCode0
Conv-CoA: Improving Open-domain Question Answering in Large Language Models via Conversational Chain-of-Action—0
Peering into the Mind of Language Models: An Approach for Attribution in Contextual Question AnsweringCode0
Aligning LLMs through Multi-perspective User Preference Ranking-based Feedback for Programming Question Answering—0
Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words?—0
Do Vision-Language Transformers Exhibit Visual Commonsense? An Empirical Study of VCR—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