arXiv AI

Benchmarking Large Language Models on Heterogeneous Cognitive and Biomedical Knowledge Graphs: The Role of Graph Grounding in Multi-Hop Reasoning and Hallucination Mitigation

arXiv AI

Aug 26

Panning for Gold: Expanding Domain-Specific Knowledge Graphs with General Knowledge

arXiv:2601.10485v5 Announce Type: replace Abstract: Domain-specific knowledge graphs (DKGs) are critical yet often suffer from limited coverage compared to General Knowledge Graphs (GKGs). Existing t...

By Runhao Zhao, Weixin Zeng, Wentao Zhang, Chong Chen, Zhengpin Li, Xiang Zhao, Lei Chen

arXiv AI

Sep 10

DrugReason: Dynamic Multi-View Reasoning over Knowledge Graph and Language Evidence for Drug Repurposing

arXiv:2609.06779v1 Announce Type: cross Abstract: Drug repurposing aims to identify new therapeutic uses for existing compounds and, compared with de novo drug discovery, offers a faster and more cos...

By Zijie Liu, Hongxuan Li, Zhen Tan, Jinhao Duan, Baixiang Huang, Zunpeng Liu, Kai Shu, Tianlong Chen

llms efficiency safety

arXiv Computation and Language

Sep 22

Knowledge-Graph Grounding Helps LLMs Only for Out-of-Training Knowledge: A Controlled Study on Clinical Question Answering

arXiv:2606.22419v3 Announce Type: replace Abstract: A recent Nature Medicine study reports that general-purpose frontier LLMs outperform specialized retrieval-augmented clinical tools on medical benc...

By Madhulatha Mandarapu, Sandeep Kunkunuru

llms rag agents nlp benchmarks

arXiv AI

22h ago

Thalamus-Reasoning: A Multimodal Large Language Model for Multi-Sample Omics Reasoning

Thalamus‑Reasoning is a 9B multimodal large language model that embeds bulk or single‑cell transcriptomes as continuous vectors, allowing them to be interleaved with natural‑language instructions and other samples. The model is trained on a large corpus that links experimental measurements to biological knowledge and task supervision, covering 157 task groups and 5.21 million conversations. It outperforms competing models on several held‑out annotation tasks, the GEO‑OmicsQA benchmark, and PerturbQA perturbation‑response prediction, demonstrating the benefit of continuous omics representations over text‑only gene lists.

By Maciej Sypetkowski, {\L}ukasz Smoli\'nski, Remigiusz Kinas, Joanna Krawczyk, Bart{\l}omiej Hofman, Aleksandra Mo\.zwi{\l}{\l}o, Micha{\l} Pikusa, Tomasz Jetka, Rafa{\l} Powalski

llms rag fine-tuning multimodal benchmarks

arXiv Machine Learning

Jun 8

GraphWalker: Patient Analogy Meets Information Gain for Clinical Reasoning with Large Language Models

arXiv:2604. 06684v2 Announce Type: replace Abstract: Clinical reasoning over electronic health records (EHRs) is a fundamental yet challenging task in modern healthcare.

By Yue Fang, Weibin Liao, Yuxin Guo, Jiaran Gao, Hongxin Ding, Jinyang Zhang, Xinke Jiang, Zhibang Yang, Junfeng Zhao, Yasha Wang, Liantao Ma

llms agents benchmarks

arXiv AI

Jul 17

Enhancing Small Language Models Reasoning through Knowledge Graph Grounding

arXiv:2607. 14149v1 Announce Type: new Abstract: Although large language models (LLMs) have set benchmarks for zero-shot reasoning, their deployment remains cost-prohibitive and environmentally taxing.

By Dimitrios Kelesis, Konstantinos Bougiatiotis, Georgios Paliouras

llms agents benchmarks

arXiv Machine Learning

Jul 17

NeuroGRIP: Retrieval-Augmented Graph Refinement for Knowledge-Grounded EEG Seizure Diagnosis

arXiv:2607. 14314v1 Announce Type: new Abstract: Seizure diagnosis from EEG signals is a critical yet persistently challenging task, due to the complicated neural dynamics and the spurious connections in inter-channel modeling.

By Lincan Li, Zheng Chen, Yushun Dong

llms rag safety

Hugging Face Trending Papers

Sep 2

HyGRAIL: Cost-Aware and Evidence-Grounded Scientific Hypothesis Discovery over Knowledge Graphs

Scientific knowledge graphs organize entities and relations extracted from scientific literature, but they remain inherently incomplete. Missing typed links in such graphs can therefore represent plau...

llms agents benchmarks

arXiv AI

Jun 16

DeepRoot: A KG-Coordinated Multi-Agent System for Therapeutic Reasoning over Historical Medical Texts

arXiv:2606. 15931v1 Announce Type: cross Abstract: Historical medical archives and traditional medicines hold immense potential for drug discovery and remain a primary source for current drug development.

By Zijian Carl Ma, Sean J. Wang, Sijbren Kramer, Li Erran Li

llms rag agents

arXiv AI

Jun 19

Detecting Hallucinations for Large Language Model-based Knowledge Graph Reasoning

arXiv:2606. 19351v1 Announce Type: cross Abstract: Knowledge graph (KG) reasoning infers new knowledge from existing facts and is widely applied in question answering, recommendation, and decision support.

By Xinyan Zhu, Yaoqi Liu, Yue Gao, Huadong Ma, Cheng Yang, Chuan Shi

llms nlp benchmarks safety

arXiv Machine Learning

Jun 16

Semantic Reasoning in Medicine: The Role of Knowledge Graphs Across Five Key Domains

arXiv:2606. 15155v1 Announce Type: new Abstract: Knowledge graphs (KGs) have emerged as a promising solution for integrating and reasoning over complex biomedical and clinical data in healthcare.

By Haniye Sherafatmandjoo, Mohammad Akbari, Zahed Rahmati

nlp safety

arXiv Machine Learning

Jun 2

OncoReason: Structuring Clinical Reasoning in LLMs for Robust and Interpretable Survival Prediction

arXiv:2510. 17532v2 Announce Type: replace-cross Abstract: Predicting cancer treatment outcomes requires models that are both accurate and interpretable, particularly in the presence of heterogeneous clinical data.

By Raghu Vamshi Hemadri, Geetha Krishna Guruju, Kristi Topollai, Anna Ewa Choromanska

llms nlp reinforcement-learning fine-tuning benchmarks safety

Related stories