SOTAVerified

Common Sense Reasoning

Common sense reasoning tasks are intended to require the model to go beyond pattern recognition. Instead, the model should use "common sense" or world knowledge to make inferences.

Papers

Showing 251300 of 939 papers

TitleStatusHype
A framework for mining lifestyle profiles through multi-dimensional and high-order mobility feature clustering0
FusionSense: Bridging Common Sense, Vision, and Touch for Robust Sparse-View Reconstruction0
FVQA 2.0: Introducing Adversarial Samples into Fact-based Visual Question Answering0
Distributional semantics for ontology verification0
Gaze-Enabled Egocentric Video Summarization via Constrained Submodular Maximization0
Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection0
Cooperating with Machines0
Ambiguss, a game for building a Sense Annotated Corpus for French0
Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules0
Stereotype Detection in LLMs: A Multiclass, Explainable, and Benchmark-Driven Approach0
AbductionRules: Training Transformers to Explain Unexpected Inputs0
Conversational AI : Open Domain Question Answering and Commonsense Reasoning0
Converging Measures and an Emergent Model: A Meta-Analysis of Human-Automation Trust Questionnaires0
Attentioned Convolutional LSTM InpaintingNetwork for Anomaly Detection in Videos0
A Tool for Extracting Conversational Implicatures0
ContextGPT: Infusing LLMs Knowledge into Neuro-Symbolic Activity Recognition Models0
A mathematical theory of super-resolution and two-point resolution0
Affordance Extraction and Inference based on Semantic Role Labeling0
From Common Sense Reasoning to Neural Network Models through Multiple Preferences: an overview0
Context-based Natural Language Processing for GIS-based Vague Region Visualization0
Content selection as semantic-based ontology exploration0
ATLAS: Learning to Optimally Memorize the Context at Test Time0
Bridging Visual Perception with Contextual Semantics for Understanding Robot Manipulation Tasks0
Constructing a Dictionary Describing Feature Changes of Arguments in Event Sentences0
A Theory of Human-Like Few-Shot Learning0
A Machine Consciousness architecture based on Deep Learning and Gaussian Processes0
Constrained Text Generation with Global Guidance -- Case Study on CommonGen0
Consolidating Commonsense Knowledge0
A Systematic Survey of Text Worlds as Embodied Natural Language Environments0
Conflict-driven Inductive Logic Programming0
Concept Induction using LLMs: a user experiment for assessment0
A Systematic Survey of Text Worlds as Embodied Natural Language Environments0
Affective Computing in the Era of Large Language Models: A Survey from the NLP Perspective0
Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs0
Good Automatic Authentication Question Generation0
ConceptAgent: LLM-Driven Precondition Grounding and Tree Search for Robust Task Planning and Execution0
A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions0
Co-NavGPT: Multi-Robot Cooperative Visual Semantic Navigation Using Vision Language Models0
Computing Sentiment Scores of Verb Phrases for Vietnamese0
A Survey on Semantics in Automated Data Science0
A Logic-based Approach for Recognizing Textual Entailment Supported by Ontological Background Knowledge0
Computational principles of intelligence: learning and reasoning with neural networks0
Computational Argumentation: A Journey Beyond Semantics, Logic, Opinions, and Easy Tasks0
A Logical Model for Supporting Social Commonsense Knowledge Acquisition0
Comprehensive Annotation of Various Types of Temporal Information on the Time Axis0
Comprehension Based Question Answering using Bloom’s Taxonomy0
A survey of Identification and mitigation of Machine Learning algorithmic biases in Image Analysis0
Affective Common Sense Knowledge Acquisition for Sentiment Analysis0
Framework for Certification of AI-Based Systems0
Comprehension Based Question Answering using Bloom's Taxonomy0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ST-MoE-32B 269B (fine-tuned)Accuracy96.1Unverified
2Unicorn 11B (fine-tuned)Accuracy91.3Unverified
3CompassMTL 567M with TailorAccuracy90.5Unverified
4CompassMTL 567MAccuracy89.6Unverified
5UnifiedQA 11B (fine-tuned)Accuracy89.4Unverified
6Claude 3 Opus (5-shot)Accuracy88.5Unverified
7GPT-4 (5-shot)Accuracy87.5Unverified
8ExDeBERTa 567MAccuracy87Unverified
9LLaMA-2 13B + MixLoRAAccuracy86.3Unverified
10LLaMA3 8B+MoSLoRAAccuracy85.8Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-4 (few-shot, k=25)Accuracy96.4Unverified
2PaLM 2 (few-shot, CoT, SC)Accuracy95.1Unverified
3Shivaay (4B, few-shot, k=8)Accuracy91.04Unverified
4StupidLLMAccuracy91.03Unverified
5Claude 2 (few-shot, k=5)Accuracy91Unverified
6Claude 1.3 (few-shot, k=5)Accuracy90Unverified
7PaLM 540B (Self Improvement, Self Consistency)Accuracy89.8Unverified
8PaLM 540B (Self Consistency)Accuracy88.7Unverified
9PaLM 540B (Self Improvement, CoT Prompting)Accuracy88.3Unverified
10PaLM 540B (Self Improvement, Standard-Prompting)Accuracy87.2Unverified
#ModelMetricClaimedVerifiedStatus
1ST-MoE-32B 269B (fine-tuned)Accuracy95.2Unverified
2LLaMA 3 8B+MoSLoRA (fine-tuned)Accuracy90.5Unverified
3PaLM 2-L (1-shot)Accuracy89.7Unverified
4PaLM 2-M (1-shot)Accuracy88Unverified
5LLaMA-3 8B + MixLoRAAccuracy86.5Unverified
6Camelidae-8×34BAccuracy86.2Unverified
7PaLM 2-S (1-shot)Accuracy85.6Unverified
8LLaMA 65B + CFG (0-shot)Accuracy84.2Unverified
9GAL 120B (0-shot)Accuracy83.8Unverified
10LLaMA-2 13B + MixLoRAAccuracy83.5Unverified
#ModelMetricClaimedVerifiedStatus
1Turing NLR v5 XXL 5.4B (fine-tuned)EM95.9Unverified
2ST-MoE-32B 269B (fine-tuned)EM95.1Unverified
3T5-11BF194.1Unverified
4DeBERTa-1.5BEM94.1Unverified
5PaLM 540B (finetuned)EM94Unverified
6Vega v2 6B (fine-tuned)EM93.9Unverified
7PaLM 2-L (one-shot)F193.8Unverified
8T5-XXL 11B (fine-tuned)EM93.4Unverified
9PaLM 2-M (one-shot)F192.4Unverified
10PaLM 2-S (one-shot)F192.1Unverified