SOTAVerified

Logical Reasoning

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–250 of 747 papers

TitleStatusHype
LLM-Aided Efficient Hardware Design Automation—0
Improving Small-Scale Large Language Models Function Calling for Reasoning Tasks—0
Aligning CodeLLMs with Direct Preference Optimization—0
MedLogic-AQA: Enhancing Medical Question Answering with Abstractive Models Focusing on Logical StructuresCode0
Do Large Language Models Truly Grasp Mathematics? An Empirical Exploration From Cognitive Psychology—0
Uncovering Autoregressive LLM Knowledge of Thematic Fit in Event RepresentationCode0
From Babbling to Fluency: Evaluating the Evolution of Language Models in Terms of Human Language AcquisitionCode0
Exploiting LLMs' Reasoning Capability to Infer Implicit Concepts in Legal Information Retrieval—0
"Let's Argue Both Sides": Argument Generation Can Force Small Models to Utilize Previously Inaccessible Reasoning Capabilities—0
Boosting Deductive Reasoning with Step Signals In RLHF—0
Transformer-based Language Models for Reasoning in the Description Logic ALCQ—0
A Systematic Assessment of OpenAI o1-Preview for Higher Order Thinking in Education—0
P-FOLIO: Evaluating and Improving Logical Reasoning with Abundant Human-Written Reasoning Chains—0
uto\!L: Autonomous Evaluation of LLMs for Truth Maintenance and Reasoning Tasks—0
HLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation PredictionCode0
KnowGraph: Knowledge-Enabled Anomaly Detection via Logical Reasoning on Graph Data—0
Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical ReasoningCode1
Automatic Curriculum Expert Iteration for Reliable LLM ReasoningCode1
Think Beyond Size: Adaptive Prompting for More Effective Reasoning—0
Can Transformers Reason Logically? A Study in SAT Solving—0
Which Programming Language and What Features at Pre-training Stage Affect Downstream Logical Inference Performance?Code0
TurtleBench: Evaluating Top Language Models via Real-World Yes/No PuzzlesCode2
GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language ModelsCode1
Latent Feature Mining for Predictive Model Enhancement with Large Language Models—0
Interpret Your Decision: Logical Reasoning Regularization for Generalization in Visual ClassificationCode0
Deliberate Reasoning for LLMs as Structure-aware Planning with Accurate World Model—0
Learning from Committee: Reasoning Distillation from a Mixture of Teachers with Peer-ReviewCode2
GraphIC: A Graph-Based In-Context Example Retrieval Model for Multi-Step Reasoning—0
CodePMP: Scalable Preference Model Pretraining for Large Language Model Reasoning—0
RATIONALYST: Pre-training Process-Supervision for Improving ReasoningCode1
BabelBench: An Omni Benchmark for Code-Driven Analysis of Multimodal and Multistructured DataCode0
Wait, but Tylenol is Acetaminophen... Investigating and Improving Language Models' Ability to Resist Requests for Misinformation—0
Logic-of-Thought: Injecting Logic into Contexts for Full Reasoning in Large Language ModelsCode0
Judgment of Thoughts: Courtroom of the Binary Logical Reasoning in Large Language Models—0
Strategies for Improving NL-to-FOL Translation with LLMs: Data Generation, Incremental Fine-Tuning, and VerificationCode0
LTNtorch: PyTorch Implementation of Logic Tensor NetworksCode2
Thought-Path Contrastive Learning via Premise-Oriented Data Augmentation for Logical Reading ComprehensionCode0
GroupDebate: Enhancing the Efficiency of Multi-Agent Debate Using Group Discussion—0
Enhancing Logical Reasoning in Large Language Models through Graph-based Synthetic DataCode0
LogicPro: Improving Complex Logical Reasoning via Program-Guided LearningCode0
ProSLM : A Prolog Synergized Language Model for explainable Domain Specific Knowledge Based Question Answering—0
Video Token Sparsification for Efficient Multimodal LLMs in Autonomous Driving—0
Unleash LLMs Potential for Recommendation by Coordinating Twin-Tower Dynamic Semantic Token Generator—0
KARGEN: Knowledge-enhanced Automated Radiology Report Generation Using Large Language Models—0
CauseJudger: Identifying the Cause with LLMs for Abductive Logical Reasoning—0
Action is the primary key: a categorical framework for episode description and logical reasoning—0
VProChart: Answering Chart Question through Visual Perception Alignment Agent and Programmatic Solution ReasoningCode1
Testing and Evaluation of Large Language Models: Correctness, Non-Toxicity, and Fairness—0
LLM-Based Multi-Hop Question Answering with Knowledge Graph Integration in Evolving Environments—0
LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language ModelsCode1
Show:102550
← PrevPage 5 of 15Next →
All datasetsLingOlyBIG-bench (Formal Fallacies Syllogisms Negation)BIG-bench (Penguins In A Table)BIG-bench (Reasoning About Colored Objects)BIG-bench (Temporal Sequences)BIG-bench (Logic Grid Puzzle)BIG-bench (StrategyQA)RuWorldTreeWinograd AutomaticBIG-bench (Logical Fallacy Detection)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Claude OpusDelta_NoContext28.8—Unverified
2GPT-4oDelta_NoContext25.1—Unverified
3Gemini 1.5 ProDelta_NoContext23.4—Unverified
4GPT-4Delta_NoContext21.5—Unverified
5Command R+Delta_NoContext11.6—Unverified
6GPT-3.5Delta_NoContext11.2—Unverified
7Mixtral 8x7BDelta_NoContext6.4—Unverified
8Llama 3 8BDelta_NoContext4.9—Unverified
9Llama 3 70BDelta_NoContext2.9—Unverified
10Gemma 7BDelta_NoContext2.2—Unverified
#ModelMetricClaimedVerifiedStatus
1PaLM 2 (few-shot, k=3, Direct)Accuracy64.8—Unverified
2PaLM 2 (few-shot, k=3, CoT)Accuracy57.2—Unverified
3OPT 66B (few-shot, k=3)Accuracy54—Unverified
4PaLM 540B (few-shot, k=3)Accuracy53.6—Unverified
5GPT-NeoX 20B (few-shot, k=3)Accuracy52.8—Unverified
6BLOOM 176B (few-shot, k=3)Accuracy52.8—Unverified
7Chinchilla-70B (few-shot, k=5)Accuracy52.1—Unverified
8Bloomberg GPT 50B (few-shot, k=3)Accuracy50.8—Unverified
9Gopher-280B (few-shot, k=5)Accuracy50.7—Unverified
#ModelMetricClaimedVerifiedStatus
1PaLM 2 (few-shot, k=3, CoT)Accuracy84.9—Unverified
2PaLM 2 (few-shot, k=3, Direct)Accuracy65.8—Unverified
3Chinchilla-70B (few-shot, k=5)Accuracy48.7—Unverified
4PaLM 540B (few-shot, k=3)Accuracy44.5—Unverified
5Gopher-280B (few-shot, k=5)Accuracy40.6—Unverified
6BLOOM 176B (few-shot, k=3)Accuracy40.41—Unverified
7Bloomberg GPT (few-shot, k=3)Accuracy37.67—Unverified
8GPT-NeoX (few-shot, k=3)Accuracy33.56—Unverified
9OPT 66B (few-shot, k=3)Accuracy28.08—Unverified
#ModelMetricClaimedVerifiedStatus
1PaLM 2 (few-shot, k=3, CoT)Accuracy91.2—Unverified
2PaLM 2 (few-shot, k=3, Direct)Accuracy61.2—Unverified
3Chinchilla-70B (few-shot, k=5)Accuracy59.7—Unverified
4Gopher-280B (few-shot, k=5)Accuracy49.2—Unverified
5PaLM 540B (few-shot, k=3)Accuracy38—Unverified
6BLOOM 176B (few-shot, k=3)Accuracy36.8—Unverified
7Bloomberg GPT (few-shot, k=3)Accuracy34.8—Unverified
8OPT 66B (few-shot, k=3)Accuracy31.2—Unverified
9GPT-NeoX (few-shot, k=3)Accuracy26—Unverified
#ModelMetricClaimedVerifiedStatus
1PaLM 2 (few-shot, k=3, CoT)Accuracy100—Unverified
2PaLM 2 (few-shot, k=3, Direct)Accuracy96.4—Unverified
3PaLM 540B (few-shot, k=3)Accuracy39.6—Unverified
4BLOOM 176B (few-shot, k=3)Accuracy36.8—Unverified
5Chinchilla-70B (few-shot, k=5)Accuracy32—Unverified
6Bloomberg GPT (few-shot, k=3)Accuracy29.2—Unverified
7OPT 66B (few-shot, k=3)Accuracy23.6—Unverified
8GPT-NeoX (few-shot, k=3)Accuracy21.2—Unverified
9Gopher-280B (few-shot, k=5)Accuracy19—Unverified
#ModelMetricClaimedVerifiedStatus
1Chinchilla-70B (few-shot, k=5)Accuracy44—Unverified
2PaLM-540B (few-shot, k=5)Accuracy42.4—Unverified
3PaLM-62B (few-shot, k=5)Accuracy36.5—Unverified
4Gopher-280B (few-shot, k=5)Accuracy35.1—Unverified
#ModelMetricClaimedVerifiedStatus
1PaLM-540B (few-shot, k=5)Accuracy73.9—Unverified
2Chinchilla-70B (few-shot, k=5)Accuracy68.3—Unverified
3PaLM-62B (few-shot, k=5)Accuracy65.4—Unverified
4Gopher-280B (few-shot, k=5)Accuracy61—Unverified
#ModelMetricClaimedVerifiedStatus
1Human benchmarkAccuracy 83.7—Unverified
2RuGPT-3 LargeAccuracy 40.7—Unverified
3RuGPT-3 MediumAccuracy 38—Unverified
4RuGPT-3 SmallAccuracy 34—Unverified
#ModelMetricClaimedVerifiedStatus
1Human benchmarkAccuracy87—Unverified
2RuGPT-3 SmallAccuracy57.9—Unverified
3RuGPT-3 MediumAccuracy57.2—Unverified
4RuGPT-3 LargeAccuracy55.5—Unverified
#ModelMetricClaimedVerifiedStatus
1Chinchilla-70B (few-shot, k=5)Accuracy72.1—Unverified
2Gopher-280B (few-shot, k=5)Accuracy58.9—Unverified