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 5251–5300 of 10817 papers

TitleStatusHype
QASnowball: An Iterative Bootstrapping Framework for High-Quality Question-Answering Data Generation—0
Adapting Large Language Models to Domains via Reading Comprehension—0
Syntax Tree Constrained Graph Network for Visual Question Answering—0
PDFTriage: Question Answering over Long, Structured Documents—0
Multimodal Multi-Hop Question Answering Through a Conversation Between Tools and Efficiently Finetuned Large Language Models—0
Enhancing Large Language Model Induced Task-Oriented Dialogue Systems Through Look-Forward Motivated Goals—0
NOWJ1@ALQAC 2023: Enhancing Legal Task Performance with Classic Statistical Models and Pre-trained Language Models—0
Sorted LLaMA: Unlocking the Potential of Intermediate Layers of Large Language Models for Dynamic Inference—0
Monolingual or Multilingual Instruction Tuning: Which Makes a Better AlpacaCode0
Silver Retriever: Advancing Neural Passage Retrieval for Polish Question Answering—0
Data Distribution Bottlenecks in Grounding Language Models to Knowledge BasesCode0
Structural Self-Supervised Objectives for TransformersCode0
D3: Data Diversity Design for Systematic Generalization in Visual Question AnsweringCode0
Investigating Answerability of LLMs for Long-Form Question Answering—0
Feature Engineering in Learning-to-Rank for Community Question Answering Task—0
Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?—0
CATfOOD: Counterfactual Augmented Training for Improving Out-of-Domain Performance and CalibrationCode0
Evaluating the Ebb and Flow: An In-depth Analysis of Question-Answering Trends across Diverse Platforms—0
Rank2Tell: A Multimodal Driving Dataset for Joint Importance Ranking and Reasoning—0
NeCo@ALQAC 2023: Legal Domain Knowledge Acquisition for Low-Resource Languages through Data Enrichment—0
Two is Better Than One: Answering Complex Questions by Multiple Knowledge Sources with Generalized Links—0
Textbooks Are All You Need II: phi-1.5 technical report—0
AGent: A Novel Pipeline for Automatically Creating Unanswerable QuestionsCode0
Duplicate Question Retrieval and Confirmation Time Prediction in Software Communities—0
MMHQA-ICL: Multimodal In-context Learning for Hybrid Question Answering over Text, Tables and Images—0
LLMCad: Fast and Scalable On-device Large Language Model Inference—0
Evaluation and Enhancement of Semantic Grounding in Large Vision-Language Models—0
Enhancing Pipeline-Based Conversational Agents with Large Language Models—0
Introducing "Forecast Utterance" for Conversational Data Science—0
Interpretable Visual Question Answering via Reasoning Supervision—0
Aligning Large Language Models for Clinical TasksCode0
HC3 Plus: A Semantic-Invariant Human ChatGPT Comparison CorpusCode0
GRASS: Unified Generation Model for Speech-to-Semantic Tasks—0
Exploiting Language Models as a Source of Knowledge for Cognitive Agents—0
ATM: Action Temporality Modeling for Video Question Answering—0
Physically Grounded Vision-Language Models for Robotic Manipulation—0
AVATAR: Robust Voice Search Engine Leveraging Autoregressive Document Retrieval and Contrastive Learning—0
Understanding Video Scenes through Text: Insights from Text-based Video Question Answering—0
LeanContext: Cost-Efficient Domain-Specific Question Answering Using LLMs—0
Multilingual Text Representation—0
Towards Addressing the Misalignment of Object Proposal Evaluation for Vision-Language Tasks via Semantic GroundingCode0
BatchPrompt: Accomplish more with lessCode0
Expanding Frozen Vision-Language Models without Retraining: Towards Improved Robot Perception—0
Distraction-free Embeddings for Robust VQA—0
DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew—0
Separate and Locate: Rethink the Text in Text-based Visual Question AnsweringCode0
Affective Visual Dialog: A Large-Scale Benchmark for Emotional Reasoning Based on Visually Grounded Conversations—0
KGConv, a Conversational Corpus grounded in Wikidata—0
Challenges of GPT-3-based Conversational Agents for Healthcare—0
Biomedical Entity Linking with Triple-aware Pre-Training—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