LLM Grounding

LLM: Large Language Model

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25 papers in the last four weeks, up 127% on the four weeks before. 0.2% of all new papers.

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Latest papers 216

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Natural Language Questions as an Interface for Knowledge Graphs: QRAKEN Graph Distillation and Semantic Self-Healing
Oct 6, 2026Remo Grillo, Lukas Klic, Giovanni ColavizzaLLM Grounding Knowledge Graphs
University of Bologna, Via Zamboni 33, 40126 Bologna, Italy · I Tatti — The Harvard University Center for Italian Renaissance Studies, Via di Vincigliata 26, 50135 Florence, Italy · Department of Communication, University of Copenhagen, Karen Blixens Plads 8, 2300 Copenhagen S, Denmark
LOGIC: An LLM Benchmark for Intent-Grounded Change Impact in Aerospace Electrical Systems
Oct 6, 2026Muhammad Faraz Shoaib, Muhammad Qasim, Raisulhaq Mohammed Rizwan +3LLM Grounding
School of Computing Wichita State University 1845 Fairmount St. Wichita, KS 67260 · School of Computing Department of Biomedical Engineering Wichita State University 1845 Fairmount St. Wichita, KS 67260 · School of Computing Department of Industrial Engineering Wichita State University 1845 Fairmount St. Wichita, KS 67260
VERITYGATE: A Four-Gate Schema-Level Faithfulness Framework and Paired Benchmark for Grounded LLM Narrations over Structured Evidence
Sep 30, 2026Sachin GuptaLLM Evaluation LLM Grounding
Independent Researcher San Jose, California, USA
Network-based Spatial Context Retrieval for Open-weight LLMs: A Faithfulness Benchmark for Grounded Geographic Reasoning
Sep 30, 2026Joan PerezSpatial Reasoning Benchmarks LLM Grounding
Urban Geo Analytics
Concept-Grounded Attention: A Controlled Evaluation of Graph-Injected Attention, Temporal Versioning, and Epistemic Status
Sep 30, 2026Sachin Dev Duggal, Pradyumna Swarnalatha Ramanna, Alexandros VassiliadesLLM Grounding Temporal Reasoning in Language Models
SeKondBrain AI Labs, London, United Kingdom.
CARAT: Do Materials LLMs Reason or Recite?
Sep 29, 2026Jiajun Wu, Jian Yang, Zixiang Ni +2LLM Evaluation LLM Grounding
Beihang University · Xi’an Jiaotong University · Imperial College London +1
FORGE: Form-Optimal Routing of Grounded Evidence for Frozen LLM Agents
Sep 28, 2026Xi Xiao, Yunbei Zhang, Chen Liu +7LLM Grounding LLM Inference Scheduling
University of Alabama at Birmingham
Large Language Models for Structured Clinical Data Analysis: Dual-Agent Grounding and Validation
Sep 28, 2026Erfan D. Dehkalani, Seetha Shankaran, Abbot R. Laptook +3Multi-Agent LLM Systems LLM Grounding
Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, and Harvard Medical School, Boston, MA, USA · Department of Pediatrics, Wayne State University School of Medicine, Detroit, MI, USA · Department of Pediatrics, Women & Infants Hospital of Rhode Island, and Warren Alpert Medical School of Brown University, Providence, RI, USA +1
DISCO: Distributed Long Context Scaling with Grounding-Reasoning Disaggregation
Sep 27, 2026Guanzheng Chen, Viet Dac Lai, Subhojyoti Mukherjee +5LLM Grounding Long-Context Language Model Inference
National University of Singapore · Adobe Research
TelecomGPT-R1: Unified Post-Training for Reasoning Across Heterogeneous Telecom Tasks
Sep 21, 2026Bohao Wang, Chenwei Wu, Hang Zou +7LLM Grounding RL for Language Model Reasoning
College of Information Science and Electronic Engineering, Zhejiang University, 310027 Hangzhou, China · Research Institute for Digital Future, Khalifa University, P O Box 127788, Abu Dhabi, UAE · Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109-2122, USA +1
Potential for Enhanced Learning in Machine Learning Classes by Using Wiki LLM Indexing
Sep 21, 2026Brian WrightRetrieval-Augmented Generation LLM Grounding
School of Data Science, University of Virginia
The Copy Ceiling: An Input-Exposure Control for Ontology-Grounded Generation over Curated Corpora
Sep 21, 2026John J. O'HareGrounded Text Generation LLM Evaluation
DreamLab AI, The Loom / VisionFlow neurosymbolic stack
Schema-Anchored Latent Reasoning for Semantic Parsing-Based Knowledge Base Question Answering
Sep 17, 2026Guangze Gao, Zixuan Li, Sikui Zhang +5LLM Grounding Knowledge Graph Question Answering
Institute of Automation, Chinese Academy of Sciences China · Institute of Computing Technology, Chinese Academy of Sciences China · University of Chinese Academy of Sciences China
Code-as-Auditor: Executable Compliance Reasoning via Regulation-to-Code
Sep 16, 2026Jisoo Kim, Taeyoon Kwack, Jinwoo Jang +2LLM Grounding Legal Reasoning
Sungkyunkwan University Suwon, Republic of Korea
BENCHCOMPASS: From Scores to Signals for Training and Harness Decisions in Payment-Domain LLMs
Sep 16, 2026Sijie Dong, Wei Ren, Xuanwei Hu +9Financial Services LLM Evaluation
Ant International
What Breaks Under Pruning in Smart Homes, and When? Evaluating LLM Degradation Across Architectures and Task Complexity
Sep 15, 2026Congjing Zhang, Vashishtha Patil, Henning Lange +1LLM Grounding LLM Pruning
Alexa Home AI, Amazon.com · University of Washington
EviScope: Paired Counterfactual Evidence Diagnostics for Faithful and Efficient Grounded Language Models
Sep 15, 2026Suryadeep Singh DeswalCounterfactual Evaluation LLM Grounding
Indian Institute of Technology Roorkee Roorkee, India
Verifiable by Construction: Claim-Level Evaluation of Verbatim Citation in Clinical Question Answering
Sep 14, 2026Jiashuo Zhang, Yuling Chen, Yvonne Commodore-Mensah +1LLM Grounding LLM Answer Verification
Department of Computer Science Johns Hopkins University · School of Nursing Johns Hopkins University
Empirical Evaluation of Open-Source Large Language Models for Retrieval-Augmented Generation in ESG Domain
Sep 14, 2026Motaz Saad, Anna Borrelli, Ivan Gentile +3LLM Evaluation LLM Grounding
University of Salento · University of Naples Federico II · IFAB Foundation
Retrieval-Augmented Generation for Scientific Code Understanding
Sep 14, 2026Aaron Nobile, Andreas Adelmann, Mohsen SadrRetrieval-Augmented Generation LLM Grounding
Department of Physics, ETH Zürich, 8093 Zürich, Switzerland · Paul Scherrer Institute, 5232 Villigen PSI, Switzerland · Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Beyond ID Embeddings: Process-Grounded Language Modeling for Cognitive Diagnosis
Sep 14, 2026Minghang Liu, Yuanzhuo Wang, Qiang Qiu +2LLM Grounding Cognitive Modeling
State Key Laboratory of AI Safety, Institute of Computing Technology, CAS · University of Chinese Academy of Sciences
The Answer Path and the Grounding Instruction in LLM Question Answering over Knowledge Graphs
Sep 9, 2026Arquimedes CanedoMulti-Hop QA LLM Grounding
Siemens Digital Industries Software Princeton, NJ, USA
Evaluation of Contextual Understanding in Large Language Models
Sep 8, 2026Subavarshana Arumugam, Mamta Nallaretnam, Kithuni Wickramasinghe +4LLM Evaluation LLM Grounding
Department of Computer Science and Engineering, University of Moratuwa, Moratuwa, Sri Lanka · Department of Electrical and Computer Engineering, University of Miami, Coral Gables, Florida, USA.
Evaluating and Improving Evidence-Grounded Fact-Checking in LLMs via Multi-Round Evidence Ablation
Sep 8, 2026Xingyu Deng, Mingzi Cao, Nikolaos Aletras +2LLM Evaluation LLM Grounding
University of Sheffield · Sheffield, UK
Translation Indeterminacy and the Distributional Fallacy
Sep 7, 2026Michael CarlLLM Grounding Distributional Semantics
Kent State University Modern and Classical Language Studies
Noēsis: Deterministic-First Retrieval with Two-Tier Context Hydration for Factuality-Critical Queries on Small Local Models
Sep 7, 2026Nicola CogottiRetrieval-Augmented Generation LLM Grounding
Alpha Cogs
Corporate Language Model (CLM): Transforming Tacit and Fragmented Enterprise Knowledge into a Sovereign, Auditable, and Executable Corporate Intelligence Layer
Sep 7, 2026Fabricio C. Avini, Guilherme TrezLLM Grounding Language Modeling
Business Graduate Program – Unisinos University · Care Intelligence, Porto Alegre, Brazil
HyGRAIL: Cost-Aware and Evidence-Grounded Scientific Hypothesis Discovery over Knowledge Graphs
Sep 2, 2026Yihang Sun, Zhihan Zhu, Zhiyuan Jiang +3LLM Grounding Scientific Hypothesis Generation
University of Illinois Urbana-Champaign
Architecting Conversational Data Systems for Stateless LLM APIs: The Hydration Proxy Pattern
Sep 1, 2026Joseph AxisaLLM Grounding LLM Serving
Google Cloud · California, USA
Candidate Generation and Definition-Guided Verification for Sentence-Level Depression Symptom Recognition
Sep 1, 2026Weiming Li, Catarina Barata, Miguel Constante +1LLM Grounding Depression Detection
Institute for Systems and Robotics (ISR), LARSyS, Departamento de Bioengenharia, Instituto Superior Técnico (IST), 1049-001 Lisboa. Portugal · Institute for Systems and Robotics (ISR), LARSyS, Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, Portugal · Department of Psychiatry, Hospital Beatriz Ângelo, 2674-514 Loures, Portugal

Oct 6, 2026, cs.AIJ/K move · Enter open · S save

Natural Language Questions as an Interface for Knowledge Graphs: QRAKEN Graph Distillation and Semantic Self-Healing

Remo Grillo, Lukas Klic, Giovanni Colavizza

University of Bologna, Via Zamboni 33, 40126 Bologna, Italy · I Tatti — The Harvard University Center for Italian Renaissance Studies, Via di Vincigliata 26, 50135 Florence, Italy · Department of Communication, University of Copenhagen, Karen Blixens Plads 8, 2300 Copenhagen S, Denmark

LLM Grounding Knowledge Graphs Natural Language to SPARQL

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Natural-language access to RDF knowledge graphs is a core Semantic Web ambition. Large language models (LLMs) have advanced Text-to-SPARQL, yet on unfamiliar graphs they often generate valid queries that misrepresent the populated data model. QRAKEN is a training-free, ontology-agnostic neurosymbolic pipeline grounding generation in empirical graph evidence rather than schema expectations. An offline distiller produces TTQL, a compact description of populated multi-hop patterns, conditional frequencies and path-conditioned literal examples, plus a class-property co-occurrence matrix. Online, TTQL guides the LLM, while deterministic syntax, vocabulary and data-model checks provide diagnostics for iterative refinement. On CK25 (First International Text2SPARQL Challenge), under matched-condition recomputation on a QLever snapshot, QRAKEN achieves strict F1 of 0.643

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0.026 with GPT-4.1 mini and 0.652

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0.012 with GPT-5.4: relative gains of 30% and 32% over the strongest recomputed participant, outperforming systems using the same base model family. Ablations identify TTQL patterns as the dominant driver (+0.31 strict F1 over a shape-only baseline); the refinement loop provides a cheap safety net, rejecting triple patterns unsupported by the co-occurrence matrix. Compared with auto-derived SHACL, TTQL yields 64% higher strict F1, supporting the value of empirical patterns beyond schema exposure. With two local 35B 4-bit open-weight models at zero marginal cost, the same pipeline matches the strongest recomputed participant, and TTQL advantages over shape-only and SHACL baselines persist. Results on a single, relatively small benchmark provide an initial empirical signal; monolithic TTQL injection on very open cross-domain graphs remains the main limitation.

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