Logical Reasoning
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Benchmarks
Most implemented
Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphs
PaLM: Scaling Language Modeling with Pathways
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Large Language Models are Zero-Shot Reasoners
Papers
Rewarding Novel Deductions: Solver-guided Process Supervision for Logical Reasoning
Logical reasoning remains a major challenge for large language models (LLMs), particularly on structured problems that require precise constraint tracking, consistency preservation, and multi-step deduction. This challen…
Logical ReasoningDODR: Deterministic Operator-Driven Reasoning in Latent Space
Autoregressive (AR) large language models formulate reasoning as token-level probabilistic sampling, which induces three fundamental defects in complex logical reasoning: error accumulation, probability substituting nece…
Logical ReasoningBeyond Surface Forms: Symbolic Edits as a Test for Logical Reasoning with LLMs
Logical reasoning with large language models (LLMs) is a critical capability, as it reflects a system's ability to correctly deduce hypotheses from a given context using faithful deductive processes. However, LLM reasoni…
Logical ReasoningSymbolLKG: Towards Verifiable Logical Reasoning via Logical Knowledge Graph and Symbolic Solvers
Large Language Models (LLMs) have demonstrated remarkable proficiency in natural language understanding, yet they struggle with strict multi-step reasoning, frequently suffering from hallucinations and inconsistency. Exi…
Natural Language UnderstandingLogical ReasoningNo Judgment Without a Reason: Counterfactual Receipts for Versioned AI Evaluators
Evaluators often produce correct labels via flawed reasoning, a critical failure for agentic systems gating actions, routing reviews, or supplying training feedback. Standard evaluation only verifies final label correctn…
Logical ReasoningTowards general embodied intelligence: integrating large language models, knowledge bases, and reasoning capabilities to build the next generation of AI agents
The convergence of large language models (LLMs), structured knowledge bases (KBs), and reasoning ability (RA) presents a promising trajectory toward general embodied intelligence (GEI). This paper reviews the evolution o…
Continual LearningLogical Reasoning