The paper introduces CodeGraph, an open‑taxonomy knowledge graph that semantically annotates source code by extracting entities such as algorithms, paradigms, design patterns, and application domains from millions of files. Using a specialized large language model and a three‑stage Wikidata linking process, the authors ground these entities in Wikidata and construct a graph with about 158 million nodes and 1 billion typed edges across 14 programming languages. A quality‑assurance protocol combining human evaluation and an LLM‑as‑a‑judge filter quantifies annotation precision.
By Federico Pennino, Andrea Gurioli, Stefano Zacchiroli, Maurizio Gabbrielli, Paolo Ferragina
INDRA is a research platform that integrates multiple archival collections—such as UCSF’s Industry Documents Library, Columbia and CUNY’s ToxicDocs, and Stanford’s SRITA—into a single, LLM‑readable corpus. It employs three safeguards: a closed evidentiary sandbox, real‑time provenance tagging, and a deterministic system‑level protocol to ensure that model outputs are clearly distinguished from archival evidence and from the model’s own inferences. The platform enables large‑language‑model‑powered investigations across these archives while keeping the conditions of knowledge production transparent and auditable.
By Daniel Akselrad, Robert N. Proctor
arXiv:2609.16519v1 Announce Type: new
Abstract: Scientific research increasingly relies on large, heterogeneous data sources, motivating interest in retrieval-augmented generation (RAG) systems that...
By Bernie Boscoe, Srinath Saikrishnan, Vikram Seenivasan, Jack Stark, Andrew Lizarraga, Morgan Himes, Jonathan Soriano, PJ Allen, Tuan Do
arXiv:2608.23263v1 Announce Type: new
Abstract: The FAIR Digital Object (FDO) framework mandates that metadata attribute values be expressed as persistent identifiers (PIDs) wherever possible, to pro...
By Zeyd Boukhers, Lingxiao Kong, Xenophon Zabulis, Georgios Toubekis
Scientific research increasingly relies on large, heterogeneous data sources, motivating interest in retrieval-augmented generation (RAG) systems that provide natural language access to scientific kno...
The FAIR Digital Object (FDO) framework mandates that metadata attribute values be expressed as persistent identifiers (PIDs) wherever possible, to produce a fully machine-actionable graph in which ev...
arXiv:2610.17110v1 Announce Type: cross
Abstract: AI-assisted research leaves instructions, computations, artifact revisions and checks whose relationships matter when another researcher receives the...
By Wen Ouyang, Bocheng Huang, Qianyu Yao, Fei Sun, Minying Deng, Haoyue Cheng, Wenwen Zhou, Lei Mou, Yusi Wei, Jiang Li, Kun Zhu, Lei Wang, Yi Feng, Jiaheng Dai, Ke Qian, Dan Wang, Yahui Wang, Chenyi Wang, Mingsheng Lyu, Yaqiang Zhang, Ping Zheng, Chunhua Tang, Xinge Ma, Xu Zhang, Youjia Fan, Can Lu, Zhijun Dai, Man Hu, Qiqi Xie, Beinan Liu, Yuanning Guo, Yunze Liu, Jinhong Jiang, Xianjun Fu, Mingwei Zhang, Yuanji Xu, Shilin Xia, Bowen Yang, Mingjun Yu, Jingdun Xie, Xuwei Chen, Xia Zou, Yuzhou Xue, Jianguo Zhou, Chunhao Cao, Donghao Tian, Lei Huang, Jinxiao Li, Shengrong Long, Zefeng Song, Honglin Li, Jiang Luo, Wenying Jiang, Shanshan Li, Lei Dai, Ning Jiang, Ying Cai, Chaohui Li, Chunyan Peng, Hetong Zhao, Angqing Li, Chunyan Yang, Chongyang Sun, Yong Li, Xinyu Shi, Wei Dai, Ming Peng, Chen Sang, Yuanyuan Han, Desong Qiu, Haixin Miao, Jian Xu, Yi Chen, Xiaoliang Shi, Tian Shen, Teng Hu, Shuhao Wang, Yingyong Hou, Huimei Wang
The paper presents a system that transforms open‑problem listings in research fields into a structured, queryable knowledge graph. It combines a hand‑curated problem layer with an evidence layer derived from bibliographic data, linked through typed, provenance‑carrying connections. The authors evaluate the approach on database and AI problem catalogs, showing that the new graph can answer all previously answerable queries and additional ones about recent work, but also reveal limitations in automated status judgments, leading to a design recommendation that status changes must be proposed with evidence and reviewed by humans.
By Madhulatha Mandarapu, Sandeep Kunkunuru
arXiv:2508. 12232v5 Announce Type: replace-cross Abstract: Issue-to-commit link recovery in software repositories is fundamental to software traceability and project management, yet it remains a challenging task.
By Arshia Akhavan, Alireza Hoseinpour, Abbas Heydarnoori, Hamid Bagheri, Mehdi Keshani
SpecMine is a large-scale corpus that documents Spec-Driven Development (SDD) artifacts in public GitHub repositories. It includes a broad census of 470,795 spec files from 73,030 repositories linked to 17 tools, a focused census of 98,574 Kiro layout files from 12,910 repositories, and a sweep of 5,992 pull requests across 581 repositories that modify specs. The dataset provides enriched metadata, full commit histories, parsed document structures, and over 2.4 million typed references connecting specs to code, sibling documents, PRs, branches, and issues.
By Shyam Agarwal, Anmol Singhal, Travis Breaux, Bogdan Vasilescu
The paper presents a knowledge layer that reorganizes enterprise Retrieval-Augmented Generation (RAG) for multi‑agent systems by placing an ontology at the artifact level rather than on extracted entities. Using a seven‑agent reverse‑engineering pipeline, the authors processed 241 repositories across 18 services to generate thousands of artifacts that capture scope, journeys, rules, and acceptance criteria, each tagged with provenance metadata. The resulting self‑describing catalog, sparse metadata registry, and navigation hypergraph enable queries to resolve to artifact identifiers, thereby structurally disambiguating near‑identical rules and improving retrieval accuracy. The system was built in under a week and helped root‑cause over 100 production defects and attribute 35 release regressions to specific rules and services.
By Garima Agrawal, Prasun Das, Akshay Sarvade, Priyanka L, Minisha N, Sravani Joshna, Hemath Manivannan, Lavanya Korada, Sambhrit Pattanayak, Srashti Gupta, Siddu R, Prasad Kalyanasundaram
arXiv:2609.16498v1 Announce Type: cross
Abstract: Research data repositories are essential infrastructure for scientific inquiry and for ensuring that datasets follow FAIR (Findable, Accessible, Inte...
By Daniel Ebanks, Devika Jain