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 401–450 of 939 papers

TitleStatusHype
Is the Elephant Flying? Resolving Ambiguities in Text-to-Image Generative Models—0
CAPE: Corrective Actions from Precondition Errors using Large Language Models—0
Galactica: A Large Language Model for ScienceCode4
Eliciting Knowledge from Large Pre-Trained Models for Unsupervised Knowledge-Grounded ConversationCode0
Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models—0
GradSkip: Communication-Accelerated Local Gradient Methods with Better Computational ComplexityCode0
LMPriors: Pre-Trained Language Models as Task-Specific Priors—0
Large Language Models Can Self-Improve—0
Commonsense Knowledge from Scene Graphs for Textual Environments—0
Deep Bidirectional Language-Knowledge Graph PretrainingCode2
Behavior Cloned Transformers are Neurosymbolic ReasonersCode1
Task Compass: Scaling Multi-task Pre-training with Task PrefixCode1
Perplexity from PLM Is Unreliable for Evaluating Text Quality—0
A survey of Identification and mitigation of Machine Learning algorithmic biases in Image Analysis—0
Guess the Instruction! Flipped Learning Makes Language Models Stronger Zero-Shot LearnersCode1
Large Language Models are Pretty Good Zero-Shot Video Game Bug DetectorsCode1
Robot Task Planning and Situation Handling in Open Worlds—0
Modular Approach to Machine Reading Comprehension: Mixture of Task-Aware Experts—0
KC-ISA: An Implicit Sentiment Analysis Model Combining Knowledge Enhancement and Context FeaturesCode0
COMMA-DEER: COmmon-sense Aware Multimodal Multitask Approach for Detection of Emotion and Emotional Reasoning in Conversations—0
Do ever larger octopi still amplify reporting biases? Evidence from judgments of typical colour—0
Decentralized Vehicle Coordination: The Berkeley DeepDrive Drone Dataset and Consensus-Based Models—0
ERNIE-mmLayout: Multi-grained MultiModal Transformer for Document Understanding—0
Assessment of cognitive characteristics in intelligent systems and predictive ability—0
The Embeddings World and Artificial General Intelligence—0
Leveraging Large (Visual) Language Models for Robot 3D Scene UnderstandingCode1
Elaboration-Generating Commonsense Question Answering at ScaleCode0
JARVIS: A Neuro-Symbolic Commonsense Reasoning Framework for Conversational Embodied Agents—0
On Reality and the Limits of Language Data: Aligning LLMs with Human Norms—0
Exploiting Sentiment and Common Sense for Zero-shot Stance DetectionCode0
Intrinsically Motivated Learning of Causal World Models—0
AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq ModelCode2
TextWorldExpress: Simulating Text Games at One Million Steps Per SecondCode1
PASTA: A Dataset for Modeling Participant States in Narratives—0
Neuro-Symbolic Learning: Principles and Applications in Ophthalmology—0
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language ModelsCode0
V-Coder: Adaptive AutoEncoder for Semantic Disclosure in Knowledge Graphs—0
Rethinking Alignment in Video Super-Resolution TransformersCode1
Reasoning about Actions over Visual and Linguistic Modalities: A Survey—0
N-Grammer: Augmenting Transformers with latent n-gramsCode4
Multi-label Classification with High-rank and High-order Label CorrelationsCode1
Ask Me What You Need: Product Retrieval using Knowledge from GPT-3—0
Is “My Favorite New Movie” My Favorite Movie? Probing the Understanding of Recursive Noun Phrases—0
A Systematic Survey of Text Worlds as Embodied Natural Language Environments—0
PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about ChangeCode2
0/1 Deep Neural Networks via Block Coordinate Descent—0
Symbolic image detection using scene and knowledge graphsCode0
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsCode4
Extracting Zero-shot Common Sense from Large Language Models for Robot 3D Scene Understanding—0
RELATE: Generating a linguistically inspired Knowledge Graph for fine-grained emotion classification—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