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 4001–4050 of 10817 papers

TitleStatusHype
Augmenting Black-box LLMs with Medical Textbooks for Biomedical Question Answering (Published in Findings of EMNLP 2024)Code1
Understanding Video Scenes through Text: Insights from Text-based Video Question Answering—0
AVATAR: Robust Voice Search Engine Leveraging Autoregressive Document Retrieval and Contrastive Learning—0
CRUISE-Screening: Living Literature Reviews ToolboxCode1
Can I Trust Your Answer? Visually Grounded Video Question AnsweringCode1
Generative Data Augmentation using LLMs improves Distributional Robustness in Question AnsweringCode3
MedChatZH: a Better Medical Adviser Learns from Better InstructionsCode1
Multilingual Text Representation—0
LeanContext: Cost-Efficient Domain-Specific Question Answering Using LLMs—0
BatchPrompt: Accomplish more with lessCode0
Towards Addressing the Misalignment of Object Proposal Evaluation for Vision-Language Tasks via Semantic GroundingCode0
Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction FollowingCode2
Distraction-free Embeddings for Robust VQA—0
Separate and Locate: Rethink the Text in Text-based Visual Question AnsweringCode0
Expanding Frozen Vision-Language Models without Retraining: Towards Improved Robot Perception—0
DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew—0
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
Bridging the KB-Text Gap: Leveraging Structured Knowledge-aware Pre-training for KBQACode1
Biomedical Entity Linking with Triple-aware Pre-Training—0
UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and MemoryCode1
Towards Vision-Language Mechanistic Interpretability: A Causal Tracing Tool for BLIPCode1
Generations of Knowledge Graphs: The Crazy Ideas and the Business Impact—0
Empowering Cross-lingual Abilities of Instruction-tuned Large Language Models by Translation-following demonstrationsCode0
MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records—0
Rethinking Language Models as Symbolic Knowledge Graphs—0
Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question AnsweringCode1
Modeling Uncertainty and Using Post-fusion as Fallback Improves Retrieval Augmented Generation with LLMs—0
CALM : A Multi-task Benchmark for Comprehensive Assessment of Language Model BiasCode1
DLIP: Distilling Language-Image Pre-training—0
Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and BeyondCode5
An approach based on Open Research Knowledge Graph for Knowledge Acquisition from scientific papers—0
FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question AnsweringCode1
EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE—0
Evaluation of Faithfulness Using the Longest Supported Subsequence—0
Bridging the Gap: Deciphering Tabular Data Using Large Language Model—0
InstructionGPT-4: A 200-Instruction Paradigm for Fine-Tuning MiniGPT-4Code1
Towards CausalGPT: A Multi-Agent Approach for Faithful Knowledge Reasoning via Promoting Causal Consistency in LLMsCode3
Exploring the Effectiveness of GPT Models in Test-Taking: A Case Study of the Driver's License Knowledge Test—0
HopPG: Self-Iterative Program Generation for Multi-Hop Question Answering over Heterogeneous Knowledge—0
Knowledge Graph Prompting for Multi-Document Question AnsweringCode2
VQA Therapy: Exploring Answer Differences by Visually Grounding AnswersCode0
Large Language Models on Wikipedia-Style Survey Generation: an Evaluation in NLP ConceptsCode0
DocPrompt: Large-scale continue pretrain for zero-shot and few-shot document question answering—0
Using Large Language Models for Cybersecurity Capture-The-Flag Challenges and Certification Questions—0
SCULPT: Shape-Conditioned Unpaired Learning of Pose-dependent Clothed and Textured Human Meshes—0
RaLLe: A Framework for Developing and Evaluating Retrieval-Augmented Large Language ModelsCode1
Simple Baselines for Interactive Video Retrieval with Questions and AnswersCode1
Generic Attention-model Explainability by Weighted Relevance Accumulation—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