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Logical Reasoning

Papers

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Showing 401–450 of 747 papers

TitleStatusHype
HEIE: MLLM-Based Hierarchical Explainable AIGC Image Implausibility Evaluator—0
HelpSteer3: Human-Annotated Feedback and Edit Data to Empower Inference-Time Scaling in Open-Ended General-Domain Tasks—0
HF4Rec: Human-Like Feedback-Driven Optimization Framework for Explainable Recommendation—0
HopRAG: Multi-Hop Reasoning for Logic-Aware Retrieval-Augmented Generation—0
HoT: Highlighted Chain of Thought for Referencing Supporting Facts from Inputs—0
How to Make a BLT Sandwich? Learning to Reason towards Understanding Web Instructional Videos—0
How Transformers Solve Propositional Logic Problems: A Mechanistic Analysis—0
How Truncating Weights Improves Reasoning in Language Models—0
Human Comprehensible Active Learning of Genome-Scale Metabolic Networks—0
Human-in-the-Loop through Chain-of-Thought—0
HyperTree Planning: Enhancing LLM Reasoning via Hierarchical Thinking—0
HypoML: Visual Analysis for Hypothesis-based Evaluation of Machine Learning Models—0
Identifying Features that Shape Perceived Consciousness in Large Language Model-based AI: A Quantitative Study of Human Responses—0
I-Design: Personalized LLM Interior Designer—0
Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy—0
Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning—0
Improving Complex Reasoning over Knowledge Graph with Logic-Aware Curriculum Tuning—0
Improving Small-Scale Large Language Models Function Calling for Reasoning Tasks—0
Inference-Time Computations for LLM Reasoning and Planning: A Benchmark and Insights—0
Inferring User Preferences by Probabilistic Logical Reasoning over Social Networks—0
Infi-MMR: Curriculum-based Unlocking Multimodal Reasoning via Phased Reinforcement Learning in Multimodal Small Language Models—0
Instantiation-based Formalization of Logical Reasoning Tasks using Language Models and Logical Solvers—0
Interactive Visual Assessment for Text-to-Image Generation Models—0
Interleaved Reasoning for Large Language Models via Reinforcement Learning—0
CogReact: A Reinforced Framework to Model Human Cognitive Reaction Modulated by Dynamic Intervention—0
Modeling Human Decision-making: An Overview of the Brussels Quantum Approach—0
Motion-R1: Chain-of-Thought Reasoning and Reinforcement Learning for Human Motion Generation—0
MTMT: Consolidating Multiple Thinking Modes to Form a Thought Tree for Strengthening LLM—0
MUC-driven Feature Importance Measurement and Adversarial Analysis for Random Forest—0
Multimodal-to-Text Prompt Engineering in Large Language Models Using Feature Embeddings for GNSS Interference Characterization—0
Multi-source Meta Transfer for Low Resource Multiple-Choice Question Answering—0
Multi-Stage Retrieval for Operational Technology Cybersecurity Compliance Using Large Language Models: A Railway Casestudy—0
Multi-Step Inference for Reasoning Over Paragraphs—0
NAIL: A Challenging Benchmark for Na\"ive Logical Reasoning—0
Natural Language as Policies: Reasoning for Coordinate-Level Embodied Control with LLMs—0
Navigating the Dual Facets: A Comprehensive Evaluation of Sequential Memory Editing in Large Language Models—0
Negation: A Pink Elephant in the Large Language Models' Room?—0
Neural Logic Analogy Learning—0
Neural Logic Networks—0
Neural Networks and Continuous Time—0
Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning—0
Neural Tensor Networks with Diagonal Slice Matrices—0
Neurosymbolic AI: The 3rd Wave—0
Neuro-Symbolic Spatio-Temporal Reasoning—0
New Directions in Vector Space Models of Meaning—0
Non-monotonic Logical Reasoning Guiding Deep Learning for Explainable Visual Question Answering—0
Not wacky vs. definitely wacky: A study of scalar adverbs in pretrained language models—0
Object-Oriented Dynamic Networks—0
Two-stage Rule-induction Visual Reasoning on RPMs with an Application to Video Prediction—0
On Memorization of Large Language Models in Logical Reasoning—0
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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