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 226–250 of 939 papers

TitleStatusHype
Automatic Text Generation by Learning from Literary Structures—0
Multimodal Analysis Of Google Bard And GPT-Vision: Experiments In Visual Reasoning—0
Creative Captioning: An AI Grand Challenge Based on the Dixit Board Game—0
A Vision for Semantically Enriched Data Science—0
Deep Distilling: automated code generation using explainable deep learning—0
Creating 'Full-Stack' Hybrid Reasoning Systems that Prioritize and Enhance Human Intelligence—0
A vision-grounded dataset for predicting typical locations for verbs—0
AUTO-DISCERN: Autonomous Driving Using Common Sense Reasoning—0
Deep Style Match for Complementary Recommendation—0
Deep Unsupervised Hashing with Latent Semantic Components—0
DEEPYANG at SemEval-2020 Task 4: Using the Hidden Layer State of BERT Model for Differentiating Common Sense—0
Back to Square One: Artifact Detection, Training and Commonsense Disentanglement in the Winograd Schema—0
DELTA: Decomposed Efficient Long-Term Robot Task Planning using Large Language Models—0
CO-STAR: Conceptualisation of Stereotypes for Analysis and Reasoning—0
A Unified Model for Video Understanding and Knowledge Embedding with Heterogeneous Knowledge Graph Dataset—0
A Multi-Attention based Neural Network with External Knowledge for Story Ending Predicting Task—0
Despite "super-human" performance, current LLMs are unsuited for decisions about ethics and safety—0
Exploring and Analyzing Machine Commonsense Benchmarks—0
Detecting COVID-19 Conspiracy Theories with Transformers and TF-IDF—0
LLM-Advisor: An LLM Benchmark for Cost-efficient Path Planning across Multiple Terrains—0
Developing a concept-level knowledge base for sentiment analysis in Singlish—0
Augmenting Autotelic Agents with Large Language Models—0
DialogSum Challenge: Summarizing Real-Life Scenario Dialogues—0
Ecological Semantics: Programming Environments for Situated Language Understanding—0
Augmented Translation: A New Approach to Combining Human and Machine Capabilities—0
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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