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 76100 of 939 papers

TitleStatusHype
AbductionRules: Training Transformers to Explain Unexpected InputsCode1
IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language ModelsCode1
A Dataset for Interactive Vision-Language Navigation with Unknown Command FeasibilityCode1
Hierarchical Prompting Taxonomy: A Universal Evaluation Framework for Large Language Models Aligned with Human Cognitive PrinciplesCode1
HAZARD Challenge: Embodied Decision Making in Dynamically Changing EnvironmentsCode1
HeadlineCause: A Dataset of News Headlines for Detecting CausalitiesCode1
Guess the Instruction! Flipped Learning Makes Language Models Stronger Zero-Shot LearnersCode1
Guiding Pretraining in Reinforcement Learning with Large Language ModelsCode1
How Can We Know When Language Models Know? On the Calibration of Language Models for Question AnsweringCode1
KagNet: Knowledge-Aware Graph Networks for Commonsense ReasoningCode1
Learning Long-term Visual Dynamics with Region Proposal Interaction NetworksCode1
Generating similes effortlessly like a Pro: A Style Transfer Approach for Simile GenerationCode1
Fusing Context Into Knowledge Graph for Commonsense Question AnsweringCode1
A Surprisingly Robust Trick for Winograd Schema ChallengeCode1
Fake News Detection on Social Media using Geometric Deep LearningCode1
Exploring the Benefits of Training Expert Language Models over Instruction TuningCode1
Expressive Scene Graph Generation Using Commonsense Knowledge Infusion for Visual Understanding and ReasoningCode1
Finding Effective Security Strategies through Reinforcement Learning and Self-PlayCode1
Generative Data Augmentation for Commonsense ReasoningCode1
Event2Mind for Russian: Understanding Emotions and Intents in Texts. Corpus and Model for EvaluationCode1
LLM-Coordination: Evaluating and Analyzing Multi-agent Coordination Abilities in Large Language ModelsCode1
EventPlus: A Temporal Event Understanding PipelineCode1
Grounding Consistency: Distilling Spatial Common Sense for Precise Visual Relationship DetectionCode1
Evaluating and Analyzing Relationship Hallucinations in Large Vision-Language ModelsCode1
Evidence-Aware Inferential Text Generation with Vector Quantised Variational AutoEncoderCode1
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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