LLM Reasoning with Graphs

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18 papers in the last four weeks, up 350% on the four weeks before. 0.2% of all new papers.

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LLM Explainability with Counterfactual Chains and Causal Graphs
Jun 4, 2026Nirit Nussbaum-Hoffer, Nitay Calderon, Liat Ein-Dor +1LLM Reasoning with Graphs LLM Interpretability
Faculty of Data and Decision Sciences, Technion · IBM Research
Stepwise Reasoning Enhancement for LLMs via External Subgraph Generation
Jun 3, 2026Xin Zhang, Yang Cao, Baoxing Wu +2LLM Grounding LLM Reasoning with Graphs
School of Information Science and Engineering, Chongqing Jiaotong University · School of Computer Science and Technology, Chongqing University of Posts and Telecommunications
Reasoning Structure of Large Language Models
Jun 2, 2026Frédéric Berdoz, Luca A. Lanzendörfer, Fabian Farestam +1Logical Reasoning LLM Evaluation
1ETH Zurich, Switzerland.
Code-on-Graph: Iterative Programmatic Reasoning via Large Language Models on Knowledge Graphs
Jun 2, 2026Weiwei Ding, Zixuan Li, Long Bai +7LLM Grounding LLM Reasoning with Graphs
1Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences · 2Shandong University · 3Shandong University-Weihai Research Institute of Industrial Technology
GTBench: A Curriculum-Grounded Benchmark for Evaluating LLMs as Mathematical Research Assistants in Graph Theory
Jun 2, 2026Noujoud Nader, Ibrahem Aljabea, Patrick Diehl +1Mathematical Reasoning Benchmarks LLM Reasoning with Graphs
Louisiana State University, USA · Los Alamos National Laboratory, USA · Texas A&M-Central Texas, USA
Visual Graph Scaffolds for Structural Reasoning in Large Language Models
Jun 1, 2026Runlin Lei, Xiaokui Xiao, Zhewei WeiLLM Reasoning with Graphs LLM Prompting
Renmin University of China · National University of Singapore
PlanarBench: Evaluating LLM Spatial Reasoning via Planar Graph Drawing
Jun 1, 2026Oleksandr Nikitin, Anna KravchenkoSpatial Reasoning Benchmarks LLM Evaluation
GraphARC: A Comprehensive Benchmark for Graph-Based Abstract Reasoning
May 29, 2026Saku Peltonen, August Bøgh Rønberg, Andreas Plesner +1LLM Reasoning with Graphs Synthetic Benchmark Generation
ETH Zürich Zürich, Switzerland
The Compressive Knowledge Graph Hypothesis: Which Graph Facts Matter for Scientific Hypothesis Generation?
May 26, 2026Shashwat Sourav, Viktoriia Baibakova, Sanjay Das +4LLM Grounding LLM Reasoning with Graphs
1Washington University in St. Louis · 2Oak Ridge National Laboratory · 3Lawrence Berkeley National Laboratory +1
Bounded Path Context: A Controlled Study of Visible Path History in LLM-Based Knowledge Graph Question Answering
May 26, 2026Xihang Shan, Ye LuoMulti-Hop QA LLM Reasoning with Graphs
School of Mathematical Sciences Xiamen University · School of Informatics Xiamen University
Knowledge Graph-Driven Expert-Level Reasoning for Neuroscience
May 24, 2026Jake Stephen, Niraj K. JhaKnowledge Augmentation for Language Models LLM Reasoning with Graphs
Department of Electrical and Computer Engineering, Princeton University
Reinforced Graph of Thoughts: RL-Driven Adaptive Prompting for LLMs
May 21, 2026Manuel Noah Riesen, Peter Alfred von NiederhäusernLLM Reasoning with Graphs LLM Prompting
School of Engineering and Computer Science Bern University of Applied Sciences Bern, Switzerland
Ex-GraphRAG: Interpretable Evidence Routing for Graph-Augmented LLMs
May 21, 2026Yoav Kor Sade, Arvindh Arun, Rishi Puri +2Graph Neural Networks LLM Reasoning with Graphs
Tel Aviv University · Institute for AI, University of Stuttgart · NVIDIA +1
SLASH the Sink: Sharpening Structural Attention Inside LLMs
May 11, 2026Yiming Liu, Bin Lu, Xinbing Wang +2LLM Reasoning with Graphs LLM Interpretability
Shanghai Jiao Tong University, Shanghai, China · Institute of Geographical Science and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
Teaching LLMs to See Graphs: Unifying Text and Structural Reasoning
May 11, 2026Dario VajdaLLM Reasoning with Graphs Text-Attributed Graph Learning
Faculty of Computer and Information Science University of Ljubljana
LLM-Guided Monte Carlo Tree Search over Knowledge Graphs: Composing Mechanistic Explanations for Drug-Disease Pairs
May 10, 2026Rishabh Jakhar, Michel Dumontier, Remzi CelebiLLM Reasoning with Graphs Scientific Discovery
Institute of Data Science, Department of Advanced Computing Sciences, Maastricht University, The Netherlands
Belief or Circuitry? Causal Evidence for In-Context Graph Learning
May 8, 2026Katharine Kowalyshyn, Timothy Duggan, Daniel Little +1Transformer Interpretability LLM Reasoning with Graphs
Department of Computer Science, Tufts University, Medford, United States
Revisiting Graph-Tokenizing Large Language Models: A Systematic Evaluation of Graph Token Understanding
May 5, 2026Zhongjian Zhang, Yue Yu, Mengmei Zhang +3LLM Evaluation LLM Reasoning with Graphs
Beijing University of Posts and Telecommunications · China Telecom Bestpay · Beihang University
SCPRM: A Schema-aware Cumulative Process Reward Model for Knowledge Graph Question Answering
May 4, 2026Jiujiu Chen, Yazheng Liu, Sihong Xie +1LLM Reasoning with Graphs Process Reward Models
HKUST (GZ)
Position: How can Graphs Help Large Language Models?
May 4, 2026Xiyuan Wang, Yi Hu, Yanbo Wang +2LLM Grounding Knowledge Augmentation for Language Models
Institute for Artificial Intelligence, Peking University, Beijing 100871, China · School of Computer Sciences, Beijing University of Posts and Telecommunications, Beijing 100876, China
Evaluating LLMs on Large-Scale Graph Property Estimation via Random Walks
May 2, 2026Sunil Kumar Maurya, Xin LiuLLM Evaluation LLM Reasoning with Graphs
University of Tokyo Tokyo, Japan · AIST Tokyo, Japan
Detecting Hallucinations for Large Language Model-based Knowledge Graph Reasoning
Apr 27, 2026Xinyan Zhu, Yaoqi Liu, Yue Gao +3LLM Reasoning with Graphs Hallucination in Language Models
Beijing University of Posts and Telecommunications · Tsinghua University
Don't Make the LLM Read the Graph: Make the Graph Think
Apr 24, 2026Yuqi Sun, Tianqin Meng, George Liu +4Multi-Agent Coordination Game-Playing Agents
Mindoverflow · University of Waterloo · Carnegie Mellon University +4
TRN-R1-Zero: Text-rich Network Reasoning via LLMs with Reinforcement Learning Only
Apr 21, 2026Yilun Liu, Ruihong Qiu, Zi HuangZero-Shot Learning LLM Reasoning with Graphs
School of Electrical Engineering and Computer Science The University of Queensland Brisbane, Queensland, Australia
DW-Bench: Benchmarking LLMs on Data Warehouse Graph Topology Reasoning
Apr 21, 2026Ahmed G. A. H Ahmed, C. Okan SakarLLM Evaluation LLM Reasoning with Graphs
Innosol / Bahçe¸sehir University · Department of Computer Engineering, Bahcesehir University, Turkey
GraphDC: A Divide-and-Conquer Multi-Agent System for Scalable Graph Algorithm Reasoning
Apr 18, 2026Wenjin Li, Jiaming CuiMulti-Agent LLM Systems LLM Reasoning with Graphs
Department of Computer Science, Virginia Tech
RLM-on-KG: Heuristics First, LLMs When Needed: Adaptive Retrieval Control over Mention Graphs for Scattered Evidence
Apr 18, 2026Andrea Volpini, Elie RaadMulti-Hop QA LLM Reasoning with Graphs
WordLift
Integrating Graphs, Large Language Models, and Agents: Reasoning and Retrieval
Apr 17, 2026Hamed Jelodar, Samita Bai, Mohammad Meymani +3LLM Reasoning with Graphs Graph Retrieval-Augmented Generation
Canadian Institute for Cybersecurity, Faculty of Computer Science, University of New Brunswick, Fredericton, NB E3B 9W4, Canada
Learning Dynamic Belief Graphs for Theory-of-mind Reasoning
Mar 20, 2026Ruxiao Chen, Xilei Zhao, Thomas J. Cova +2Computational Cognitive Modeling LLM Reasoning with Graphs
Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, USA · Civil and Coastal Engineering, University of Florida, Gainesville, FL, USA · School of the Environment, Society & Sustainability, University of Utah, Salt Lake City, UT, USA +1
CausalRAG2: Hierarchical Causal Knowledge Graph Design for RAG
Feb 4, 2026Nengbo Wang, Tuo Liang, Vikash Singh +6KG Construction Retrieval-Augmented Generation
Department of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH, USA · Design and Innovation Department, Case Western Reserve University, Cleveland, OH, USA

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LLM Explainability with Counterfactual Chains and Causal Graphs

Nirit Nussbaum-Hoffer, Nitay Calderon, Liat Ein-Dor, Roi Reichart

Faculty of Data and Decision Sciences, Technion · IBM Research

LLM Reasoning with Graphs LLM Interpretability Causal Structure Learning Concept-Based Explanations Causal Reasoning in Language Models Counterfactual Data Augmentation+1

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Causal graphs provide a high-level language for making mechanisms transparent. Recent work uses Large Language Models (LLMs) to recover causal graphs of external-world processes. Instead, in this paper, we use causal graphs to model LLM inference itself, providing stakeholders with a transparent view of how the model perceives and organizes high-level concepts to produce a prediction. We propose a four-phase method for constructing such graphs. Given a target LLM and a set of textual examples, our method discovers class-discriminative, human-interpretable concepts and maps each input to LLM-perceived concept states. We then introduce an MCMC-inspired counterfactual augmentation procedure that expands the sparse observational data through chains of counterfactuals. This enables stable causal discovery with

σ

-CG, yielding informative, interpretable graphs. We apply our method to three LLMs across disease diagnosis, sentiment analysis, and LLM-as-a-judge classification tasks. We evaluate the learned graphs for predictive fidelity and structural stability, and the MCMC-inspired augmentation for convergence and downstream utility. Our results show that the discovered causal graphs capture meaningful dependencies consistent with LLMs' reasoning. Together, this paper provides a foundation for concept-level explainability of LLMs.

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