graph-reasoning

[KDD 2025] Rewarding Graph Reasoning Process makes LLMs more Generalized Reasoners

Publishable notebook/reference pipeline for evidence-grounded conflict analysis over knowledge graphs.

Agent Skill for Claude: Build, query, validate, and reason over knowledge graphs. Adversarial fact validation, deterministic reasoning, JSON-LD schema.

Deterministic temporal and relational reasoning engine with historical state, contradictions, provenance, exact multi-hop reasoning, and reproducible benchmarks.

Graph-based RAG autonomous agent with dynamic task decomposition, multi-LLM support, and Ragas evaluation

GTA: Graph Theory Agent and Benchmark for Algorithmic Graph Reasoning with LLMs

Persistent semantic state engine for AI agents — knowledge graphs, dynamic RAG, semantic zoom, bidirectional natural language translation, provenance tracking, self-extending graph.

Verifier-backed abstraction invention for small formal protocol and concurrency systems with contradiction-driven ontology revision

ARIA - Adaptive Revenue Intelligence & Action. An ATLAS-class payment revenue-recovery system: maps payment dependencies as a graph, observes degradation, traces failures to root cause with evidence, selects bounded recovery actions, and measures recovered revenue against a graph-blind baseline. Deterministic, explainable, honestly evaluated.

Исследовательский код для сегментации и структурного продолжения тонких сейсмических разломов с использованием анизотропной геометрии, топологических ограничений и графового анализа LIRA.

PyTorch implementation of SPIN Road Mapper: road segmentation from aerial images using spatial and interaction space graph reasoning on stacked hourglass networks.

Typed, inspectable reasoning framework for connecting candidate ideas, evidence, peer review, and evaluation.

Knowledge Representation & Reasoning via AIML, Pytholog, and Neo4j Graph DB

Evidence-grounded recall tracing with LLM-assisted extraction, deterministic graph analysis, and auditable human review.

Explaining method for Graph-Language Models.

Self-reflective, hallucination-aware multimodal RAG for reliable vision-language reasoning.

A Proposer-Critic debate framework testing whether active verification reduces the encoding-fragility of LLM graph reasoning, benchmarked against a matched-compute majority vote on GraphQA. TAU coursework.