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 351–400 of 10817 papers

TitleStatusHype
Hungry Hungry Hippos: Towards Language Modeling with State Space ModelsCode2
Advancing Multimodal Large Language Models in Chart Question Answering with Visualization-Referenced Instruction TuningCode2
GreaseLM: Graph REASoning Enhanced Language Models for Question AnsweringCode2
Baleen: Robust Multi-Hop Reasoning at Scale via Condensed RetrievalCode2
LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale InstructionsCode2
BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical DomainsCode2
GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended TasksCode2
AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous DrivingCode2
GOFA: A Generative One-For-All Model for Joint Graph Language ModelingCode2
BlendSQL: A Scalable Dialect for Unifying Hybrid Question Answering in Relational AlgebraCode2
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical ReasoningCode2
Learning Dense Representations of Phrases at ScaleCode2
Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question AnsweringCode2
Breaking the Ceiling of the LLM Community by Treating Token Generation as a Classification for EnsemblingCode2
Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QACode2
LevelRAG: Enhancing Retrieval-Augmented Generation with Multi-hop Logic Planning over Rewriting Augmented SearchersCode2
Grounded 3D-LLM with Referent TokensCode2
ktrain: A Low-Code Library for Augmented Machine LearningCode2
Lookahead: An Inference Acceleration Framework for Large Language Model with Lossless Generation AccuracyCode2
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam GenerationCode2
GeoChat: Grounded Large Vision-Language Model for Remote SensingCode2
Generate-on-Graph: Treat LLM as both Agent and KG in Incomplete Knowledge Graph Question AnsweringCode2
GeReA: Question-Aware Prompt Captions for Knowledge-based Visual Question AnsweringCode2
GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning AbilitiesCode2
Frozen Transformers in Language Models Are Effective Visual Encoder LayersCode2
LLMGA: Multimodal Large Language Model based Generation AssistantCode2
GIT: A Generative Image-to-text Transformer for Vision and LanguageCode2
LLoCO: Learning Long Contexts OfflineCode2
From CLIP to DINO: Visual Encoders Shout in Multi-modal Large Language ModelsCode2
Free Video-LLM: Prompt-guided Visual Perception for Efficient Training-free Video LLMsCode2
FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Visual Language ModelsCode2
Long-Form Video-Language Pre-Training with Multimodal Temporal Contrastive LearningCode2
Augmenting Multimodal LLMs with Self-Reflective Tokens for Knowledge-based Visual Question AnsweringCode2
FreeVA: Offline MLLM as Training-Free Video AssistantCode2
LOVA3: Learning to Visual Question Answering, Asking and AssessmentCode2
LSceneLLM: Enhancing Large 3D Scene Understanding Using Adaptive Visual PreferencesCode2
F-LMM: Grounding Frozen Large Multimodal ModelsCode2
FlagEvalMM: A Flexible Framework for Comprehensive Multimodal Model EvaluationCode2
FortisAVQA and MAVEN: a Benchmark Dataset and Debiasing Framework for Robust Multimodal ReasoningCode2
CAT: Enhancing Multimodal Large Language Model to Answer Questions in Dynamic Audio-Visual ScenariosCode2
500xCompressor: Generalized Prompt Compression for Large Language ModelsCode2
From Redundancy to Relevance: Information Flow in LVLMs Across Reasoning TasksCode2
A Survey on Benchmarks of Multimodal Large Language ModelsCode2
MDETR - Modulated Detection for End-to-End Multi-Modal UnderstandingCode2
Fine-Grained Human Feedback Gives Better Rewards for Language Model TrainingCode2
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table UnderstandingCode2
MedAgentsBench: Benchmarking Thinking Models and Agent Frameworks for Complex Medical ReasoningCode2
Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMsCode2
Atlas: Few-shot Learning with Retrieval Augmented Language ModelsCode2
FinBERT-QA: Financial Question Answering with pre-trained BERT Language ModelsCode2
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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