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 2151–2200 of 10817 papers

TitleStatusHype
Advancing Chart Question Answering with Robust Chart Component Recognition—0
Evaluating language models as risk scoresCode1
Clinical Reading Comprehension with Encoder-Decoder Models Enhanced by Direct Preference Optimization—0
RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question AnsweringCode2
LazyLLM: Dynamic Token Pruning for Efficient Long Context LLM Inference—0
Retrieve, Summarize, Plan: Advancing Multi-hop Question Answering with an Iterative Approach—0
INDIC QA BENCHMARK: A Multilingual Benchmark to Evaluate Question Answering capability of LLMs for Indic Languages—0
QuIIL at T3 challenge: Towards Automation in Life-Saving Intervention Procedures from First-Person ViewCode0
Visual Haystacks: A Vision-Centric Needle-In-A-Haystack BenchmarkCode1
MERLIN: Multimodal Embedding Refinement via LLM-based Iterative Navigation for Text-Video Retrieval-Rerank Pipeline—0
Conversational Query Reformulation with the Guidance of Retrieved Documents—0
Multimodal Reranking for Knowledge-Intensive Visual Question Answering—0
EchoSight: Advancing Visual-Language Models with Wiki Knowledge—0
Evaluating Search Engines and Large Language Models for Answering Health QuestionsCode0
TurkishMMLU: Measuring Massive Multitask Language Understanding in TurkishCode1
Continual Learning for Temporal-Sensitive Question Answering—0
ProcTag: Process Tagging for Assessing the Efficacy of Document Instruction Data—0
BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive RetrievalCode5
Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation—0
Scientific QA System with Verifiable AnswersCode2
Video-Language Alignment via Spatio-Temporal Graph TransformerCode1
Localizing and Mitigating Errors in Long-form Question AnsweringCode0
Better RAG using Relevant Information GainCode0
A Comprehensive Evaluation of Large Language Models on Temporal Event Forecasting—0
SPINACH: SPARQL-Based Information Navigation for Challenging Real-World QuestionsCode2
Reasoning with Large Language Models, a Survey—0
TM-PATHVQA:90000+ Textless Multilingual Questions for Medical Visual Question Answering—0
Evaluating Large Language Models with fmevalCode3
Evaluation of RAG Metrics for Question Answering in the Telecom Domain—0
MixGR: Enhancing Retriever Generalization for Scientific Domain through Complementary GranularityCode1
Unraveling the Truth: Do VLMs really Understand Charts? A Deep Dive into Consistency and Robustness—0
FabGPT: An Efficient Large Multimodal Model for Complex Wafer Defect Knowledge Queries—0
Graphusion: Leveraging Large Language Models for Scientific Knowledge Graph Fusion and Construction in NLP EducationCode1
Benchmarking Vision Language Models for Cultural Understanding—0
BiasAlert: A Plug-and-play Tool for Social Bias Detection in LLMs—0
GenSco: Can Question Decomposition based Passage Alignment improve Question Answering?—0
Lost and Found: Overcoming Detector Failures in Online Multi-Object TrackingCode1
sPhinX: Sample Efficient Multilingual Instruction Fine-Tuning Through N-shot Guided Prompting—0
IoT-LM: Large Multisensory Language Models for the Internet of ThingsCode1
NativQA: Multilingual Culturally-Aligned Natural Query for LLMs—0
Bridging the Gap Between Information Seeking and Product Search Systems: Q&A Recommendation for E-commerce—0
GOFA: A Generative One-For-All Model for Joint Graph Language ModelingCode2
PersonaRAG: Enhancing Retrieval-Augmented Generation Systems with User-Centric AgentsCode2
One Stone, Four Birds: A Comprehensive Solution for QA System Using Supervised Contrastive LearningCode0
A Mathematical Framework, a Taxonomy of Modeling Paradigms, and a Suite of Learning Techniques for Neural-Symbolic SystemsCode0
CompAct: Compressing Retrieved Documents Actively for Question AnsweringCode1
DAHRS: Divergence-Aware Hallucination-Remediated SRL Projection—0
TelecomGPT: A Framework to Build Telecom-Specfic Large Language Models—0
SPIQA: A Dataset for Multimodal Question Answering on Scientific PapersCode2
Model Surgery: Modulating LLM's Behavior Via Simple Parameter EditingCode1
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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