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 126–150 of 939 papers

TitleStatusHype
Finding Effective Security Strategies through Reinforcement Learning and Self-PlayCode1
Are Large Language Models Temporally Grounded?Code1
AR-Diffusion: Auto-Regressive Diffusion Model for Text GenerationCode1
3D Visual Illusion Depth EstimationCode1
Fake News Detection on Social Media using Geometric Deep LearningCode1
Exploring the Benefits of Training Expert Language Models over Instruction TuningCode1
LLM-Coordination: Evaluating and Analyzing Multi-agent Coordination Abilities in Large Language ModelsCode1
EventPlus: A Temporal Event Understanding PipelineCode1
Evaluation Toolkit For Robustness Testing Of Automatic Essay Scoring SystemsCode1
ByteSized32: A Corpus and Challenge Task for Generating Task-Specific World Models Expressed as Text GamesCode1
Do Multilingual Language Models Think Better in English?Code1
DomainRAG: A Chinese Benchmark for Evaluating Domain-specific Retrieval-Augmented GenerationCode1
Evaluating and Analyzing Relationship Hallucinations in Large Vision-Language ModelsCode1
Expressive Scene Graph Generation Using Commonsense Knowledge Infusion for Visual Understanding and ReasoningCode1
Event2Mind for Russian: Understanding Emotions and Intents in Texts. Corpus and Model for EvaluationCode1
Evidence-Aware Inferential Text Generation with Vector Quantised Variational AutoEncoderCode1
Exploring AIGC Video Quality: A Focus on Visual Harmony, Video-Text Consistency and Domain Distribution GapCode1
Boosting Theory-of-Mind Performance in Large Language Models via PromptingCode1
Blow the Dog Whistle: A Chinese Dataset for Cant Understanding with Common Sense and World KnowledgeCode1
CBVS: A Large-Scale Chinese Image-Text Benchmark for Real-World Short Video Search ScenariosCode1
Chain of Images for Intuitively ReasoningCode1
DialogSum: A Real-Life Scenario Dialogue Summarization DatasetCode1
CommonsenseQA: A Question Answering Challenge Targeting Commonsense KnowledgeCode1
CheXWorld: Exploring Image World Modeling for Radiograph Representation LearningCode1
ConceptBert: Concept-Aware Representation for Visual Question AnsweringCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ST-MoE-32B 269B (fine-tuned)Accuracy96.1—Unverified
2Unicorn 11B (fine-tuned)Accuracy91.3—Unverified
3CompassMTL 567M with TailorAccuracy90.5—Unverified
4CompassMTL 567MAccuracy89.6—Unverified
5UnifiedQA 11B (fine-tuned)Accuracy89.4—Unverified
6Claude 3 Opus (5-shot)Accuracy88.5—Unverified
7GPT-4 (5-shot)Accuracy87.5—Unverified
8ExDeBERTa 567MAccuracy87—Unverified
9LLaMA-2 13B + MixLoRAAccuracy86.3—Unverified
10LLaMA3 8B+MoSLoRAAccuracy85.8—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-4 (few-shot, k=25)Accuracy96.4—Unverified
2PaLM 2 (few-shot, CoT, SC)Accuracy95.1—Unverified
3Shivaay (4B, few-shot, k=8)Accuracy91.04—Unverified
4StupidLLMAccuracy91.03—Unverified
5Claude 2 (few-shot, k=5)Accuracy91—Unverified
6Claude 1.3 (few-shot, k=5)Accuracy90—Unverified
7PaLM 540B (Self Improvement, Self Consistency)Accuracy89.8—Unverified
8PaLM 540B (Self Consistency)Accuracy88.7—Unverified
9PaLM 540B (Self Improvement, CoT Prompting)Accuracy88.3—Unverified
10PaLM 540B (Self Improvement, Standard-Prompting)Accuracy87.2—Unverified
#ModelMetricClaimedVerifiedStatus
1ST-MoE-32B 269B (fine-tuned)Accuracy95.2—Unverified
2LLaMA 3 8B+MoSLoRA (fine-tuned)Accuracy90.5—Unverified
3PaLM 2-L (1-shot)Accuracy89.7—Unverified
4PaLM 2-M (1-shot)Accuracy88—Unverified
5LLaMA-3 8B + MixLoRAAccuracy86.5—Unverified
6Camelidae-8×34BAccuracy86.2—Unverified
7PaLM 2-S (1-shot)Accuracy85.6—Unverified
8LLaMA 65B + CFG (0-shot)Accuracy84.2—Unverified
9GAL 120B (0-shot)Accuracy83.8—Unverified
10LLaMA-2 13B + MixLoRAAccuracy83.5—Unverified
#ModelMetricClaimedVerifiedStatus
1Turing NLR v5 XXL 5.4B (fine-tuned)EM95.9—Unverified
2ST-MoE-32B 269B (fine-tuned)EM95.1—Unverified
3T5-11BF194.1—Unverified
4DeBERTa-1.5BEM94.1—Unverified
5PaLM 540B (finetuned)EM94—Unverified
6Vega v2 6B (fine-tuned)EM93.9—Unverified
7PaLM 2-L (one-shot)F193.8—Unverified
8T5-XXL 11B (fine-tuned)EM93.4—Unverified
9PaLM 2-M (one-shot)F192.4—Unverified
10PaLM 2-S (one-shot)F192.1—Unverified