SOTAVerified

Logical Reasoning

Papers

Showing 426450 of 747 papers

TitleStatusHype
A Causality-aware Paradigm for Evaluating Creativity of Multimodal Large Language Models0
A Closer Look at the Robustness of Vision-and-Language Pre-trained Models0
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT0
Action is the primary key: a categorical framework for episode description and logical reasoning0
A Densely Connected Criss-Cross Attention Network for Document-level Relation Extraction0
Algorithmic Phase Transitions in Language Models: A Mechanistic Case Study of Arithmetic0
Aligning CodeLLMs with Direct Preference Optimization0
A Mechanistic Interpretation of Syllogistic Reasoning in Auto-Regressive Language Models0
A Mousetrap: Fooling Large Reasoning Models for Jailbreak with Chain of Iterative Chaos0
AnaLog: Testing Analytical and Deductive Logic Learnability in Language Models0
Analyzing Large language models chatbots: An experimental approach using a probability test0
An Empirical Study of Retrieval Augmented Generation with Chain-of-Thought0
A Neuro-Symbolic Approach to Multi-Agent RL for Interpretability and Probabilistic Decision Making0
A New Algorithmic Decision for Categorical Syllogisms via Caroll's Diagrams0
A New Fundamental Evidence of Non-Classical Structure in the Combination of Natural Concepts0
An Explainable Fast Deep Neural Network for Emotion Recognition0
Dspy-based Neural-Symbolic Pipeline to Enhance Spatial Reasoning in LLMs0
APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoning0
A Probabilistic Model for Discriminative and Neuro-Symbolic Semi-Supervised Learning0
Are Large Language Models Strategic Decision Makers? A Study of Performance and Bias in Two-Player Non-Zero-Sum Games0
Are LLMs Rigorous Logical Reasoner? Empowering Natural Language Proof Generation with Contrastive Stepwise Decoding0
A Report on the llms evaluating the high school questions0
Argumentation Synthesis following Rhetorical Strategies0
A separation logic for sequences in pointer programs and its decidability0
AS-ES Learning: Towards Efficient CoT Learning in Small Models0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Claude OpusDelta_NoContext28.8Unverified
2GPT-4oDelta_NoContext25.1Unverified
3Gemini 1.5 ProDelta_NoContext23.4Unverified
4GPT-4Delta_NoContext21.5Unverified
5Command R+Delta_NoContext11.6Unverified
6GPT-3.5Delta_NoContext11.2Unverified
7Mixtral 8x7BDelta_NoContext6.4Unverified
8Llama 3 8BDelta_NoContext4.9Unverified
9Llama 3 70BDelta_NoContext2.9Unverified
10Gemma 7BDelta_NoContext2.2Unverified
#ModelMetricClaimedVerifiedStatus
1PaLM 2 (few-shot, k=3, Direct)Accuracy64.8Unverified
2PaLM 2 (few-shot, k=3, CoT)Accuracy57.2Unverified
3OPT 66B (few-shot, k=3)Accuracy54Unverified
4PaLM 540B (few-shot, k=3)Accuracy53.6Unverified
5GPT-NeoX 20B (few-shot, k=3)Accuracy52.8Unverified
6BLOOM 176B (few-shot, k=3)Accuracy52.8Unverified
7Chinchilla-70B (few-shot, k=5)Accuracy52.1Unverified
8Bloomberg GPT 50B (few-shot, k=3)Accuracy50.8Unverified
9Gopher-280B (few-shot, k=5)Accuracy50.7Unverified
#ModelMetricClaimedVerifiedStatus
1PaLM 2 (few-shot, k=3, CoT)Accuracy84.9Unverified
2PaLM 2 (few-shot, k=3, Direct)Accuracy65.8Unverified
3Chinchilla-70B (few-shot, k=5)Accuracy48.7Unverified
4PaLM 540B (few-shot, k=3)Accuracy44.5Unverified
5Gopher-280B (few-shot, k=5)Accuracy40.6Unverified
6BLOOM 176B (few-shot, k=3)Accuracy40.41Unverified
7Bloomberg GPT (few-shot, k=3)Accuracy37.67Unverified
8GPT-NeoX (few-shot, k=3)Accuracy33.56Unverified
9OPT 66B (few-shot, k=3)Accuracy28.08Unverified
#ModelMetricClaimedVerifiedStatus
1PaLM 2 (few-shot, k=3, CoT)Accuracy91.2Unverified
2PaLM 2 (few-shot, k=3, Direct)Accuracy61.2Unverified
3Chinchilla-70B (few-shot, k=5)Accuracy59.7Unverified
4Gopher-280B (few-shot, k=5)Accuracy49.2Unverified
5PaLM 540B (few-shot, k=3)Accuracy38Unverified
6BLOOM 176B (few-shot, k=3)Accuracy36.8Unverified
7Bloomberg GPT (few-shot, k=3)Accuracy34.8Unverified
8OPT 66B (few-shot, k=3)Accuracy31.2Unverified
9GPT-NeoX (few-shot, k=3)Accuracy26Unverified
#ModelMetricClaimedVerifiedStatus
1PaLM 2 (few-shot, k=3, CoT)Accuracy100Unverified
2PaLM 2 (few-shot, k=3, Direct)Accuracy96.4Unverified
3PaLM 540B (few-shot, k=3)Accuracy39.6Unverified
4BLOOM 176B (few-shot, k=3)Accuracy36.8Unverified
5Chinchilla-70B (few-shot, k=5)Accuracy32Unverified
6Bloomberg GPT (few-shot, k=3)Accuracy29.2Unverified
7OPT 66B (few-shot, k=3)Accuracy23.6Unverified
8GPT-NeoX (few-shot, k=3)Accuracy21.2Unverified
9Gopher-280B (few-shot, k=5)Accuracy19Unverified
#ModelMetricClaimedVerifiedStatus
1Chinchilla-70B (few-shot, k=5)Accuracy44Unverified
2PaLM-540B (few-shot, k=5)Accuracy42.4Unverified
3PaLM-62B (few-shot, k=5)Accuracy36.5Unverified
4Gopher-280B (few-shot, k=5)Accuracy35.1Unverified
#ModelMetricClaimedVerifiedStatus
1PaLM-540B (few-shot, k=5)Accuracy73.9Unverified
2Chinchilla-70B (few-shot, k=5)Accuracy68.3Unverified
3PaLM-62B (few-shot, k=5)Accuracy65.4Unverified
4Gopher-280B (few-shot, k=5)Accuracy61Unverified
#ModelMetricClaimedVerifiedStatus
1Human benchmarkAccuracy 83.7Unverified
2RuGPT-3 LargeAccuracy 40.7Unverified
3RuGPT-3 MediumAccuracy 38Unverified
4RuGPT-3 SmallAccuracy 34Unverified
#ModelMetricClaimedVerifiedStatus
1Human benchmarkAccuracy87Unverified
2RuGPT-3 SmallAccuracy57.9Unverified
3RuGPT-3 MediumAccuracy57.2Unverified
4RuGPT-3 LargeAccuracy55.5Unverified
#ModelMetricClaimedVerifiedStatus
1Chinchilla-70B (few-shot, k=5)Accuracy72.1Unverified
2Gopher-280B (few-shot, k=5)Accuracy58.9Unverified