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

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Showing 451–500 of 939 papers

TitleStatusHype
Reconstruct the Pruned Model without Any Retraining—0
ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension—0
Student Data Paradox and Curious Case of Single Student-Tutor Model: Regressive Side Effects of Training LLMs for Personalized Learning—0
Regressor-free Molecule Generation to Support Drug Response Prediction—0
Regularizing Relation Representations by First-order Implications—0
Rehearsing Answers to Probable Questions with Perspective-Taking—0
RELATE: Generating a linguistically inspired Knowledge Graph for fine-grained emotion classification—0
Reporting delays: a widely neglected impact factor in COVID-19 forecasts—0
Representation, Learning and Reasoning on Spatial Language for Downstream NLP Tasks—0
Representing General Relational Knowledge in ConceptNet 5—0
Resolving label uncertainty with implicit generative models—0
Resolving Language and Vision Ambiguities Together: Joint Segmentation & Prepositional Attachment Resolution in Captioned Scenes—0
Resolving Language and Vision Ambiguities Together: Joint Segmentation \& Prepositional Attachment Resolution in Captioned Scenes—0
Rethinking Annotation for Object Detection: Is Annotating Small-size Instances Worth Its Cost?—0
Revisiting Citizen Science Through the Lens of Hybrid Intelligence—0
RoboCSE: Robot Common Sense Embedding—0
RoboGPT: an intelligent agent of making embodied long-term decisions for daily instruction tasks—0
RoboMamba: Efficient Vision-Language-Action Model for Robotic Reasoning and Manipulation—0
RoboScript: Code Generation for Free-Form Manipulation Tasks across Real and Simulation—0
Robots Can Multitask Too: Integrating a Memory Architecture and LLMs for Enhanced Cross-Task Robot Action Generation—0
Robot Task Planning and Situation Handling in Open Worlds—0
Robust RL with LLM-Driven Data Synthesis and Policy Adaptation for Autonomous Driving—0
Russian SuperGLUE 1.1: Revising the Lessons not Learned by Russian NLP models—0
SAGE: Smart home Agent with Grounded Execution—0
SAGE: Structured Attribute Value Generation for Billion-Scale Product Catalogs—0
Scalar Adjective Identification and Multilingual Ranking—0
ScanEdit: Hierarchically-Guided Functional 3D Scan Editing—0
Scenethesis: A Language and Vision Agentic Framework for 3D Scene Generation—0
Scientia Potentia Est -- On the Role of Knowledge in Computational Argumentation—0
Seeing is Knowing! Fact-based Visual Question Answering using Knowledge Graph Embeddings—0
Seeing the Unseen: Visual Common Sense for Semantic Placement—0
Seeing the World through Text: Evaluating Image Descriptions for Commonsense Reasoning in Machine Reading Comprehension—0
Segmentation Guided Attention Networks for Visual Question Answering—0
Semantic Parsing for Text to 3D Scene Generation—0
Semantic Segmentation of RGBD Images With Mutex Constraints—0
Semantic Vector Spaces for Broadening Consideration of Consequences—0
SemEval-2018 Task 12: The Argument Reasoning Comprehension Task—0
SemEval-2024 Task 9: BRAINTEASER: A Novel Task Defying Common Sense—0
Sense Perception Common Sense Relationships—0
Sentiment Analysis Using a Novel Human Computation Game—0
Sentiment Analysis - What are we talking about?—0
SERVAL: Synergy Learning between Vertical Models and LLMs towards Oracle-Level Zero-shot Medical Prediction—0
ShotgunWSD: An unsupervised algorithm for global word sense disambiguation inspired by DNA sequencing—0
Shrinkage Initialization for Smooth Learning of Neural Networks—0
SocialNLP 2018 EmotionX Challenge Overview: Recognizing Emotions in Dialogues—0
Soft Label PU Learning—0
SOLVE: Synergy of Language-Vision and End-to-End Networks for Autonomous Driving—0
Some Extensions of Probabilistic Logic—0
Some Preliminary Steps Towards Metaverse Logic—0
Sort Story: Sorting Jumbled Images and Captions into Stories—0
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All datasetsWinoGrandearc_challengearc_easyReCoRDCommonsenseQAPARusRuCoSRWSDBIG-bench (Causal Judgment)BIG-bench (Date Understanding)BIG-bench (Disambiguation QA)BIG-bench (Sports Understanding)

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