arXiv AI

GVD: Governed Versioning and Deduplication for Document Repositories

GVD (Governed Versioning and Deduplication) is a framework that unifies cross‑document version linking with rule‑level conflict resolution under an auditable update policy. It assigns incoming documents to version families via bidirectional rule alignment, then compares their rules against family memory to detect duplicates, contradictions, asymmetric refinements, and new knowledge, using Counterfactual Span Probing (CSP) to correct neutral misclassifications. In a test on 120 enterprise documents across 59 version families, GVD achieved an F1 of 0.97 for version‑family construction and 0.94 for rule‑level consistency, with CSP improving rule consistency from 0.90 to 0.94.

arXiv AI
Sep 2

REVISE: Validity-Guided Recovery for Online Revisions in Agent Workflows

The paper introduces “Revise”, a runtime system that performs validity-guided, fine-grained recovery for online revisions in structured agent workflows. When a revision arrives, Revise intersects the change with recorded data and control dependencies, propagates the impact through the partially executed DAG, stops invalid work, preserves unaffected progress, and recomputes only the affected region. Experiments on real coding‑agent traces and LangGraph/LLMCompiler applications show that Revise matches a latest‑version oracle, reduces model calls by up to 56%, and improves service‑level objective goodput under load.

By Ruoling Qi, Xuaner Wu, Penghang Liu, Jian Chen, Yirui Liu
arXiv AI
Sep 1

CrossAudit: A Git-Native, Cross-Vendor Audit Loop for Agentic Science

CrossAudit proposes a Git‑native, cross‑vendor audit protocol for autonomous research pipelines, ensuring each work increment is reviewed by an agent from a different vendor against a human‑written rulebook. Audit outcomes, disputes, and rulings are stored as git commits, providing a replayable, versioned supervision history. The authors implemented the protocol with GitHub Actions and Python, deployed it in a computational‑chemistry pipeline, and conducted a seeded‑defect trial that revealed differing interpretations of the same rulebook by two vendors.

By Zhaohe Dong, Yuhao Chen
arXiv AI
Sep 21

From Code Archival to Knowledge Graph: Bridging Software Heritage, COAR Notify and Wikidata

The paper introduces an end‑to‑end pipeline that harvests, validates, and models links between scholarly articles and their source code from journals such as JOSS, SoftwareX, and IPOL, as well as SIGMOD ARI reproducibility reports. It produces a curated set of 4,397 DOI‑repository pairs and defines two Wikidata‑based application profiles—one for articles and one for software—aligned with schema.org and CodeMeta. Using these profiles, the authors created 4,182 new Wikidata software items linked to their papers, while only 82 repositories were previously represented, and they demonstrate compatibility with the COAR Notify protocol for future live enrichment.

By Camillo Carlo Pellizzari di San Girolamo, Francesco Tosoni
arXiv AI
2d ago

Actions with Receipts: Jointly Binding Claims, Evidence, and Execution for Replayable Tool-Agent Auditing

The paper introduces a claim‑anchored execution contract that binds a tool‑using agent’s emitted claim to its exact source span, the ordered execution prefix that produced it, and the source version and access state observed. Each receipt contains deterministic anchors, source identifiers, offsets, hashes, quotes, and a domain‑separated execution commitment, allowing a verifier to reconstruct these bindings before semantic or task labels are joined. The contract defines seven independently testable properties and demonstrates high detection rates against cross‑object attacks, with strong performance on conflict‑aware support guard evaluations.

By Miaobo Hu, Shuhao Hu, Xiaobo Guo, Xin Wang, Bokun Wang, Yina Sa, Daren Zha, Jun Xiao
arXiv AI
Aug 19

StagedWorkspace: A Versioned Workspace for Knowledge-Work Agents

StagedWorkspace is a versioned workspace designed for knowledge‑work AI agents, ensuring that every parsed view, native file edit, and review diff is explicitly tied to a specific version of the workspace state. By binding parsed records and review diffs to content hashes of native files, the system improves performance on tasks such as OfficeQA and APEX‑Agents, achieving higher pass rates and rubric scores compared to single‑view approaches. The study demonstrates that providing dual parsed/native access and visible diffs enhances agent performance, highlighting workspace state as a key experimental variable for future benchmarks.

By Yining Hua, Hongbin Na, Yifan Zhou, Akshay Kalose, Cyrus Ayubcha, Levi Lian
arXiv AI
Jul 15

AAAI-26 Dual Submissions: Novel Challenges

arXiv:2607. 11918v1 Announce Type: cross Abstract: Dual submissions, in which identical or substantially similar papers are simultaneously submitted to one or more archival venues, without cross-citation or disclosure, are a growing problem for the AAAI Conference and other scientific publication venues.

By Kiri L. Wagstaff, Joydeep Biswas, Erich Merrill III, Bo An, Ida Camacho, David J. Crandall, Matthew E. Taylor
arXiv AI
Sep 25

Ingest-Time Fact Compilation for Cost-Efficient and Reliable Question Answering over Revised Corpora

The paper introduces ingest‑time fact compilation, an architecture that preprocesses and compiles corpus data into self‑contained facts with resolved revisions, deletions, and source trust. By storing this compiled state, query‑time models can retrieve answers directly, avoiding costly reconstruction from raw passages. Experiments show that this approach reduces read cost per question by 12.89× and token usage by 21.6× while maintaining accuracy.

By Kyle Wild, Yusuke Takahashi, Asako Uraki