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2,653 papers
By making failure cheap to locate and correct, this work is a foundation for more trustworthy long-horizon agents that learn from their own mistakes, and a practical path to overseeing increasingly autonomous AI.
This project verified that generating robust and reliable software using agentic AI requires careful practice and human supervision and demonstrated that using agentic AI workflow for software development (with its prompts and skills) can become a specification of the code that leads to cost-effective sustainability of...
Reproducibility artifact for Certifying Adversarial Robustness of Quantum Classifiers under Known-Readout Query Access, prepared for ACM CCS 2026 Round B Artifact Evaluation. Version 0.1.2-ae incorporates the validated AE maintenance fixes: explicit finite/unconditional/unknown upper-certificate states; competitor fiel...
Qector Mega: IonQ Superion 256 Walking Cat Decoder (v2.2.1 Frozen Release) Distribution Package Manifest & Technical Release Summary Archive: qector_ionq_v2_frozen_clean.zip (445 entries) Access Tier: Restricted (Proprietary / NDA Evaluation Only) Distribution License: LicenseRef-Proprietary (Redistribution Strictly Pr...
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heteroTests is an R package for heteroscedasticity diagnostics in linear-model workflows. It provides a consistent interface for classical variance diagnostics including White, Breusch-Pagan, Koenker, Goldfeld-Quandt, group-wise variance tests and ARCH-related checks, together with streaming implementations, simulation...
Abstract Minimal establishes the complete operational criterion for deleting information while preserving every admissible finite-horizon test and task value, and turns that criterion into exact certificates and executable reductions. More than one hundred independently screened and frozen suites were evaluated under c...
Artifacts for "Assessing Postcondition Completeness in Auto-Generated Function Contracts for Software Verification" submission for SAST 2026. Caio Vinícius Pereira Silveira and Mateus Felipe Tymburibá Ferreira. 11st Brazilian Symposium on Systematic and Automated Software Testing. SAST 2026. September 8--11, 2026, São...
This archive contains the derived data, harmonised labels, frozen evaluation splits, and complete numerical results supporting the study "Global maps overstate the reliability of blue-carbon credits." It provides everything required to reproduce every figure and number in the paper, and a reusable benchmark for testing...
Sixth Edition, September 2026. Proposes minimum standards for evaluating Bitcoin consensus-change proposals: submission requirements, tiered minimum review periods, code-audit standards, activation-threshold floors backed by a quantified chain-split risk model grounded in the double-spend / gambler's-ruin literature (N...
Trace-IN625 is a source-aware, literature-derived dataset of tensile properties and supporting microstructure information for additively manufactured IN625. It organizes published measurements into individually retrievable material-condition records, preserving source references, processing and heat-treatment informati...
Topological String-Gradient Theory (TSGT): Autonomous LLM Stress-Test and Critical Reconstruction Author’s Context: Let’s be completely transparent about what this manuscript actually represents. While earlier drafts of TSGT were hand-iterated and driven by my own intuitive theoretical concepts, this release is the res...
Fixed (unified_math) [breaking] replace From bounds with FromPrimitive, add software-scalar tensor ops Other (deep_causality_par) Pin the fan-out, the serial bound, and the untested configuration (deep_causality_file) Repair the three audited test defects and close the gaps behind them
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.
GPT-Lab
· gpt-lab.eu
Sep 23, 2026
Requirements in large systems rarely exist in isolation. Their meaning depends on the wider project context - other requirements, policies, decisions, tests, and implementation details. That becomes especially important when AI is used for review, because spotting a possible conflict or gap is only the beginning. ReqSpace explores how AI, visualisation, and connected project context can help reviewers understand those findings, trace the relationships behind them, and focus on the questions that…
GPT-Lab
· gpt-lab.eu
Sep 17, 2026
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
We’re launching agentic video understanding across our latest Gemini models for improved accuracy and lower costs and token usage.
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