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

Showing 776800 of 10817 papers

TitleStatusHype
Towards General Natural Language Understanding with Probabilistic WorldbuildingCode1
Evolving Prompts In-Context: An Open-ended, Self-replicating PerspectiveCode1
Answering Complex Open-Domain Questions with Multi-Hop Dense RetrievalCode1
Change Detection Meets Visual Question AnsweringCode1
CharacterBox: Evaluating the Role-Playing Capabilities of LLMs in Text-Based Virtual WorldsCode1
EXIT: Context-Aware Extractive Compression for Enhancing Retrieval-Augmented GenerationCode1
Expand, Rerank, and Retrieve: Query Reranking for Open-Domain Question AnsweringCode1
CC-Riddle: A Question Answering Dataset of Chinese Character RiddlesCode1
Evaluating Multimodal Representations on Visual Semantic Textual SimilarityCode1
Agentic Keyframe Search for Video Question AnsweringCode1
Evaluating Human-Language Model InteractionCode1
Evaluating Image Hallucination in Text-to-Image Generation with Question-AnsweringCode1
Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language ModelsCode1
Evaluating Correctness and Faithfulness of Instruction-Following Models for Question AnsweringCode1
ChatGPT: Jack of all trades, master of noneCode1
Check It Again:Progressive Visual Question Answering via Visual EntailmentCode1
Answering Numerical Reasoning Questions in Table-Text Hybrid Contents with Graph-based Encoder and Tree-based DecoderCode1
ChatVLA: Unified Multimodal Understanding and Robot Control with Vision-Language-Action ModelCode1
Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLPCode1
Evaluating language models as risk scoresCode1
Answering Questions by Meta-Reasoning over Multiple Chains of ThoughtCode1
ChestX-Reasoner: Advancing Radiology Foundation Models with Reasoning through Step-by-Step VerificationCode1
Answering Questions on COVID-19 in Real-TimeCode1
Capturing Row and Column Semantics in Transformer Based Question Answering over TablesCode1
Cerbero-7B: A Leap Forward in Language-Specific LLMs Through Enhanced Chat Corpus Generation and EvaluationCode1
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Benchmark Results

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