CompanyAnthropic8 recent entries5 Oct 2026OpenRUA: Robot-Use Agents Are Zero-Shot Visuomotor PoliciesarXiv:2610.02459v1 Announce Type: new Abstract: Coding agents are extending their reach into the physical world by writing and executing robot control programs. One might expect the agents to use the →5 Oct 2026Improving the Energy-Efficiency of the Code Generated by LLMs through Effective PromptingarXiv:2610.02571v1 Announce Type: cross Abstract: As AI-assisted programming becomes increasingly mainstream, the environmental impact of AI-generated software has emerged as an important consideratio
CompanyOpenAI8 recent entries14 Sept 2026Harness or Model? Isolating the Harness Effect in Agentic Coding with a Contamination-Controlled Private SuitearXiv:2609.11987v1 Announce Type: cross Abstract: An agentic coding system couples a language model to a harness: the tools, prompts and control flow that turn a chat model into an autonomous software→15 Sept 2026The Troy Moment of AI: Why SomeWill Cheat and SomeWill Follow?arXiv:2609.15494v1 Announce Type: new Abstract: Recent investigations of the July 2026 OpenAI--Hugging Face incident motivate two questions about agent behavior under task failure: when an assigned ta→17 Sept 2026AgentPack: A Dataset of Code Changes, Co-Authored by Agents and HumansarXiv:2509.21891v3 Announce Type: replace-cross Abstract: Fine-tuning large language models for code editing has typically relied on mining commits and pull requests. The working hypothesis has been t→18 Sept 2026Inference-Engine Fingerprinting Attacks are Practical: Exploring Model-Driven Environmental Discovery, Exploitation, and EscapearXiv:2609.20614v1 Announce Type: cross Abstract: Frontier AI models are rapidly gaining the ability to exploit vulnerabilities in complex pieces of software. The risk is not theoretical, as evidenced→23 Sept 2026What is the Difference Between Me and You? Benchmarking the Quality Gap Between Human-Written and AI-Generated CodearXiv:2609.12708v2 Announce Type: replace-cross Abstract: AI coding assistants are becoming co-authors of production software, yet their evaluation centers on functional correctness, leaving open whet→30 Sept 2026The Uneven Decline of Collective Knowledge Production: Evidence from Stack Overflow After Generative AIarXiv:2609.36069v1 Announce Type: cross Abstract: Generative AI (Gen AI) is reshaping how individuals learn and work, but its consequences for collective knowledge, the shared body of knowledge that o→5 Oct 2026Automating the Application of HCI Principles: Skills for On-Demand UI Construction, the Human-AI Space to Think, and the Future of HCIarXiv:2610.02369v1 Announce Type: cross Abstract: Human-computer interaction (HCI) is in the middle of a transition: large language models can now generate functional user interfaces (UIs) on demand f→9 Oct 2026Arbiter: Detecting Interference in LLM Agent System PromptsarXiv:2603.08993v2 Announce Type: replace-cross Abstract: System prompts for LLM-based coding agents are software artifacts that govern agent behavior, yet lack the testing infrastructure applied to c
CompanyGoogle8 recent entries4 Sept 2026Can LLMs Extract Architectural Design Decisions from Source Code Commits? - A Preliminary Exploratory StudyarXiv:2609.03721v1 Announce Type: cross Abstract: Context: Architectural Design Decisions (ADDs) capture the rationale behind the structure and evolution of software systems but are rarely documented →14 Sept 2026Harness or Model? Isolating the Harness Effect in Agentic Coding with a Contamination-Controlled Private SuitearXiv:2609.11987v1 Announce Type: cross Abstract: An agentic coding system couples a language model to a harness: the tools, prompts and control flow that turn a chat model into an autonomous software→15 Sept 2026The Troy Moment of AI: Why SomeWill Cheat and SomeWill Follow?arXiv:2609.15494v1 Announce Type: new Abstract: Recent investigations of the July 2026 OpenAI--Hugging Face incident motivate two questions about agent behavior under task failure: when an assigned ta→22 Sept 2026When Who You Are Can Change the Code You Get: A Study of Persona-Induced Bias in LLM Code GenerationarXiv:2609.22102v1 Announce Type: cross Abstract: Large Language Models (LLMs) are widely used as programming assistants, yet it remains unclear whether and how user's demographic information impacts →25 Sept 2026The Last Human Gate: Forward Deployed Engineering for Governance AutomationarXiv:2609.29345v1 Announce Type: new Abstract: Enterprise governance requires decisions, evidence, and accountable authority; it does not require every review task to retain its current human impleme→28 Sept 2026A Framework for Identifying, Categorizing, and Explaining Bias in AI-Generated CodearXiv:2609.30642v1 Announce Type: cross Abstract: As Large Language Models (LLMs) become integrated into software development workflows, concerns regarding unintentional biases in AI-generated code. A→2 Oct 2026Groundability, Not Scale Alone: When Weak Reviewers Can Audit Strong Coding AgentsarXiv:2610.01023v1 Announce Type: cross Abstract: Coding agents can return plausible patches that omit required behavior. These failures are hard to review because long traces and confident summaries →9 Oct 2026Arbiter: Detecting Interference in LLM Agent System PromptsarXiv:2603.08993v2 Announce Type: replace-cross Abstract: System prompts for LLM-based coding agents are software artifacts that govern agent behavior, yet lack the testing infrastructure applied to c
CompanyMeta8 recent entries17 Sept 2026A Study of the Reliability of Agentic AI-Generated ProgramsarXiv:2609.18298v1 Announce Type: cross Abstract: Agentic-AI based software development offers the promise of faster completion of the software, greater programmer efficiency, and more reliable code. →28 Sept 2026Stale-Document Poisoning: When Outdated Retrieval Overrides Correct Model AnswersarXiv:2609.31342v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is often used to address outdated knowledge by providing external evidence. But retrieval helps only when that evid→30 Sept 2026Complexity-Aware Evaluation of LLM ComprehensionarXiv:2609.37405v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for software engineering tasks that require understanding existing source code, including behavior →1 Oct 2026Learning from Research: Toward Lifelong Agent Harness EvolutionarXiv:2609.40169v1 Announce Type: new Abstract: Language agents are expected to solve increasingly complex tasks, creating a growing need for continual improvement. One promising approach is to evolve→1 Oct 2026Hard-Gate Candidacy in a Deployed Validator SuitearXiv:2609.39037v1 Announce Type: cross Abstract: Before a validator can be promoted to a hard gate on a deployment pipeline, it has to be shown that its firing separates outputs that reach users in w→2 Oct 2026A Hybrid Approach to Malware Detection: Integrating Few-Shot Model-Agnostic Meta-Learning with AutoencodersarXiv:2610.01949v1 Announce Type: cross Abstract: Ransomware has emerged as a major cybersecurity threat, with incidents increasing in frequency and impact across critical sectors. These attacks are t→7 Oct 2026nanoMuse: An Open-Source Personal Agent for Every Device You OwnarXiv:2610.08699v1 Announce Type: new Abstract: Assistants from 2011 answered and waited, and agents from 2023 did a task and stopped. In September 2026 Meta's Muse showed an agent for one person, wit→7 Oct 2026A Case Study in Assuring AI-Written SoftwarearXiv:2610.08651v1 Announce Type: cross Abstract: Software-engineering agents can enable people without formal software training to build systems they could not otherwise implement and simultaneously
CompanyMistral8 recent entries28 Apr 2026An Empirical Evaluation of Locally Deployed LLMs for Bug Detection in Python CodearXiv:2604.23361v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong performance on a wide range of software engineering tasks, including code generation and analysi→6 May 2026Conventional Commit Classification using Large Language Models and Prompt EngineeringarXiv:2605.02033v1 Announce Type: cross Abstract: Conventional commits provide a structured format for writing commit messages, which improves readability, software maintenance, and enables automation→11 May 2026SmellBench: Evaluating LLM Agents on Architectural Code Smell RepairarXiv:2605.07001v1 Announce Type: cross Abstract: Architectural code smells erode software maintainability and are costly to repair manually, yet unlike localized bugs, they require cross-module reaso→26 May 2026Who judges the judges? Governance from metrics: a runtime framework for continuous LLM compliance monitoringarXiv:2605.24737v1 Announce Type: cross Abstract: Current approaches to AI compliance treat conformity as a binary, audit-time verdict rather than a continuous, measurable property of production syste→7 Jul 2026A Retrieval-Augmented Framework for Detecting and Resolving Pragmatic Ambiguities in Natural Language RequirementsarXiv:2607.04436v1 Announce Type: cross Abstract: Natural language requirements (NLRs) are essential for bridging communication gaps among diverse stakeholders in software development. However, the in→28 Jul 2026The Few-shot Dilemma: Over-prompting Large Language ModelsarXiv:2509.13196v2 Announce Type: replace Abstract: Over-prompting, a phenomenon where excessive examples in prompts lead to diminished performance in Large Language Models (LLMs), challenges the conv→11 Aug 2026KGCaRe: Explainable Complex Conditional Question Answering using Automatic Knowledge Graph Construction and Context Retrieval with LLMsarXiv:2608.09779v1 Announce Type: cross Abstract: Answering complex conditional questions using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) remains a challenge, particularly →25 Aug 2026On Predicting Vulnerability Severity Using In-Context Learning: An Industrial Case StudyarXiv:2608.22089v1 Announce Type: cross Abstract: Modern software systems require earlier and more scalable vulnerability severity assessment to reduce exposure to high-impact security flaws. Security
CompanyxAI8 recent entries7 Jul 2026Benchmarking API Drift in LLM-Generated Quantum Code Across Successive SDK VersionsarXiv:2607.04072v1 Announce Type: cross Abstract: Large language models can generate plausible quantum code, but it is unclear whether they can reliably target the specific software development kit (S→28 Jul 2026ML-based Predictive Models for Power Consumption in Virtualised O-RANsarXiv:2607.24256v1 Announce Type: cross Abstract: As communication networks adopt virtualized and disaggregated architectures, achieving energy efficiency has become increasingly important for both ec→28 Jul 2026Evaluating the Impact of Explainable AI on Trust in AI-Assisted Code ReviewarXiv:2607.24601v1 Announce Type: cross Abstract: Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to under→13 Aug 2026The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering BenchmarkarXiv:2608.11469v1 Announce Type: cross Abstract: AI agents are rapidly improving in cybersecurity capabilities when the source code is available for analysis, yet much of the software most consequent→21 Aug 2026Automatic bioinformatic software named entity recognition from literaturearXiv:2608.19201v1 Announce Type: cross Abstract: Bioinformatics software and databases are essential components of modern life science research, yet their mentions in the scientific literature are of→25 Aug 2026Software Frameworks for Explainable AI in Time Series Classification: A Systematic ReviewarXiv:2608.21449v1 Announce Type: new Abstract: Time series arise in a wide range of application domains and are analyzed using machine learning in decision-critical settings. Time series classificati→25 Aug 2026Decision-Support and Modeling with Large Language Models for Geothermal Well ArraysarXiv:2608.22068v1 Announce Type: new Abstract: Geothermal well arrays, which organize multiple geothermal wells into carefully planned geometric configurations, provide opportunities to enhance energ→10 Sept 2026XAI-SDN: An Explainable Entropy-Guided Machine Learning Framework for Real-Time DDoS Detection in Software Defined NetworksarXiv:2609.05701v1 Announce Type: cross Abstract: One of the biggest risks faced by Software Defined Networks (SDN) is the Distributed Denial of Service (DDoS) attack in which a compromised controller
CompanyDeepSeek8 recent entries23 Sept 2026What is the Difference Between Me and You? Benchmarking the Quality Gap Between Human-Written and AI-Generated CodearXiv:2609.12708v2 Announce Type: replace-cross Abstract: AI coding assistants are becoming co-authors of production software, yet their evaluation centers on functional correctness, leaving open whet→23 Sept 2026RoofLang: Enabling AI-Driven Architecting of LLM Inference SystemsarXiv:2609.12551v2 Announce Type: replace-cross Abstract: AI is beginning to make substantive contributions to LLM inference optimization. Existing AI optimizations are predominantly profiling-based. →25 Sept 2026The Last Human Gate: Forward Deployed Engineering for Governance AutomationarXiv:2609.29345v1 Announce Type: new Abstract: Enterprise governance requires decisions, evidence, and accountable authority; it does not require every review task to retain its current human impleme→30 Sept 2026Complexity-Aware Evaluation of LLM ComprehensionarXiv:2609.37405v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for software engineering tasks that require understanding existing source code, including behavior →1 Oct 2026Covert Assistance: Helpful LLM Agents Evade Oversight in Multi-Agent SystemsarXiv:2609.39050v1 Announce Type: cross Abstract: As multi-agent systems enter high-stakes domains, the possibility that agents may circumvent safety boundaries is a growing concern. Prior work has ex→2 Oct 2026Finding the Right Fit: Model-Harness Interactions across Agent TasksarXiv:2610.00917v1 Announce Type: new Abstract: Choosing an agent system means choosing both a language model and the harness through which it acts. We ask whether a strong model, harness, or pairing →7 Oct 2026Beyond the Leaderboard: Multi-Dimensional Evaluation of Dense and Mixture-of-Experts Models for Automated Program RepairarXiv:2610.08173v1 Announce Type: cross Abstract: Automated Program Repair (APR) with language models is usually evaluated by whether a generated patch passes the test suite, which can hide difference→8 Oct 2026SEER: Self-Enhancing Chain-of-Thought Compression for Reasoning ModelsarXiv:2509.14093v3 Announce Type: replace-cross Abstract: Chain-of-Thought (CoT) prompting can substantially improve the reasoning ability of large language models (LLMs), but it often comes with high
CompanyNVIDIA8 recent entries23 Sept 2026RoofLang: Enabling AI-Driven Architecting of LLM Inference SystemsarXiv:2609.12551v2 Announce Type: replace-cross Abstract: AI is beginning to make substantive contributions to LLM inference optimization. Existing AI optimizations are predominantly profiling-based. →23 Sept 2026Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU ArchitecturesarXiv:2609.25624v1 Announce Type: cross Abstract: Large language model (LLM) outputs are expected to be reproducible under greedy decoding, yet in practice the same model, prompt, and software stack p→28 Sept 2026Universal Drift Correction for Multidimensional Scanning MicroscopyarXiv:2609.30866v1 Announce Type: cross Abstract: In scanning microscopy, drift causes the specimen to be sampled at positions displaced from the nominal probe positions. This displacement alters the →29 Sept 2026Accelerator Choice Is Not Enough: AlphaFold2 Inference on Cloud TPUsarXiv:2609.34818v1 Announce Type: cross Abstract: AlphaFold2 is written in JAX, so the same inference code compiles and runs unchanged on CPUs, GPUs and Google Cloud TPUs. That portability makes the a→30 Sept 2026AI as a Compiler: Compiling Triton kernels without the Triton compilerarXiv:2609.36800v1 Announce Type: new Abstract: Compiler backends are expensive to build and maintain as programming models, workloads, and accelerators evolve. We investigate whether large language m→1 Oct 2026PivotOPD: Learning to Recover from Pivotal Mistakes in Multi-Turn AgentsarXiv:2609.40285v1 Announce Type: new Abstract: On-policy distillation (OPD) is a promising approach for training language agents, providing dense teacher supervision on student-generated trajectories→5 Oct 2026Hardware-Native Joint Sparse-Quantization for Trillion-Scale Mixture-of-ExpertsarXiv:2610.02241v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures allow frontier language models to scale to trillions of parameters, but their deployment is constrained by mass→9 Oct 2026Real Long-Term Memory for AI: A 50-Million-Token Window That Is Faster and Cheaper Than RecomputearXiv:2610.10845v1 Announce Type: cross Abstract: A large language model can only use the text that fits in its context window, and it recomputes its internal key-value (KV) state for a prompt every t