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 301–350 of 939 papers

TitleStatusHype
Declarative Reasoning on Explanations Using Constraint Logic ProgrammingCode0
PointLLM: Empowering Large Language Models to Understand Point CloudsCode2
Towards One-Shot Learning for Text Classification using Inductive Logic ProgrammingCode0
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language ModelsCode2
CHORUS: Learning Canonicalized 3D Human-Object Spatial Relations from Unbounded Synthesized Images—0
A Review on Objective-Driven Artificial Intelligence—0
Multimodal Analysis Of Google Bard And GPT-Vision: Experiments In Visual Reasoning—0
Token-Scaled Logit Distillation for Ternary Weight Generative Language ModelsCode1
KETM:A Knowledge-Enhanced Text Matching methodCode1
LLaMA-E: Empowering E-commerce Authoring with Object-Interleaved Instruction Following—0
Bootstrapping Developmental AIs: From Simple Competences to Intelligent Human-Compatible AIs—0
Vocab-Expander: A System for Creating Domain-Specific Vocabularies Based on Word Embeddings—0
dPASP: A Comprehensive Differentiable Probabilistic Answer Set Programming Environment For Neurosymbolic Learning and Reasoning—0
Do Multilingual Language Models Think Better in English?Code1
When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities—0
An Overview Of Temporal Commonsense Reasoning and Acquisition—0
"Tidy Up the Table": Grounding Common-sense Objective for Tabletop Object Rearrangement—0
Integrating a Heterogeneous Graph with Entity-aware Self-attention using Relative Position Labels for Reading Comprehension Model—0
Drive Like a Human: Rethinking Autonomous Driving with Large Language ModelsCode2
Retrieval Augmented Generation using Engineering Design KnowledgeCode0
Model Card and Evaluations for Claude Models—0
Piecing Together Clues: A Benchmark for Evaluating the Detective Skills of Large Language Models—0
Some Preliminary Steps Towards Metaverse Logic—0
GPT4RoI: Instruction Tuning Large Language Model on Region-of-InterestCode2
Garbage in, garbage out: Zero-shot detection of crime using Large Language ModelsCode0
Stay on topic with Classifier-Free Guidance—0
REFLECT: Summarizing Robot Experiences for Failure Explanation and CorrectionCode1
Kernel Choice Matters for Boundary Inference Using Local Polynomial Density: With Application to Manipulation Testing—0
Knowledge-Driven Robot Program Synthesis from Human VR DemonstrationsCode0
Multi-CLIP: Contrastive Vision-Language Pre-training for Question Answering tasks in 3D Scenes—0
Being Right for Whose Right Reasons?Code0
AWQ: Activation-aware Weight Quantization for LLM Compression and AccelerationCode6
Large Language Models Are Not Strong Abstract ReasonersCode1
What does the Failure to Reason with "Respectively" in Zero/Few-Shot Settings Tell Us about Language Models?—0
PlaSma: Making Small Language Models Better Procedural Knowledge Models for (Counterfactual) PlanningCode1
Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and MemoryCode2
MEMEX: Detecting Explanatory Evidence for Memes via Knowledge-Enriched ContextualizationCode0
ByteSized32: A Corpus and Challenge Task for Generating Task-Specific World Models Expressed as Text GamesCode1
Editing Common Sense in TransformersCode0
ImageNetVC: Zero- and Few-Shot Visual Commonsense Evaluation on 1000 ImageNet CategoriesCode1
LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language ModelsCode2
The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-TuningCode2
Augmenting Autotelic Agents with Large Language Models—0
PlugMed: Improving Specificity in Patient-Centered Medical Dialogue Generation using In-Context Learning—0
Reasoning Implicit Sentiment with Chain-of-Thought PromptingCode1
PaLM 2 Technical Report—0
AR-Diffusion: Auto-Regressive Diffusion Model for Text GenerationCode1
Translating SUMO-K to Higher-Order Set Theory—0
Leveraging Large Language Models in Conversational Recommender Systems—0
Exploiting Pseudo Image Captions for Multimodal Summarization—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