Search: “software”

From Mathematical to Executable Certificates for Machine Unlearning

arXiv:2610.02268v1 Announce Type: new Abstract: Machine unlearning is needed when data must be removed because of deletion requests, outdated records, or data-quality concerns, while retraining from s

researcharxiv-cs-lg

5 Oct 2026

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Scaling Trajectories for Complex Tasks through Recursive Self-Rewrite

DGX agent

arXiv:2610.02826v1 Announce Type: new Abstract: Successful trajectories on difficult tasks provide valuable supervision for model improvement, but specialized harnesses introduce interventions that ma

model-releasesarxiv-cs-ai

5 Oct 2026

Securing Computer-Use Agents Against Branch Steering Attacks

arXiv:2610.03089v1 Announce Type: cross Abstract: Modern Computer Use Agents (CUAs) directly interact with graphical user interfaces and execute third-party web tools, exposing them to indirect prompt

5 Oct 2026

Verifiable, Articulable, and Tacit Components of Preference

arXiv:2610.03025v1 Announce Type: new Abstract: What makes a short story gripping; a news article newsworthy; or a math proof elegant? These constructs resist articulation or verification; their meani

5 Oct 2026

Safety

A Deterministic and Auditable AI Security Risk Assessment Framework with ATLAS Aligned Executable Rules and Formal Verification

arXiv:2610.01436v1 Announce Type: new Abstract: Artificial intelligence systems are increasingly deployed in high impact and safety critical settings, yet security assessment remains difficult to repr

safetyarxiv-cs-ai

Applications

A Hybrid Approach to Malware Detection: Integrating Few-Shot Model-Agnostic Meta-Learning with Autoencoders

arXiv: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

applicationsarxiv-cs-ai

ALFRED: Requirement-driven development of an open-source mobile manipulator for long-term plant monitoring

model-releasesarxiv-cs-cv

arXiv:2610.01477v1 Announce Type: cross Abstract: Tracking seasonal change in crops and forests requires observing the same plants repeatedly. Ground robots can do this at close range, and a manipulat

Safety

Beyond State-of-the-Art: Standardising Environmental Impact Metrics for AI Research

arXiv:2610.01116v1 Announce Type: new Abstract: As the capabilities and ubiquity of Large Language Models (LLMs) grow, so does their environmental footprint. Despite calls for responsible AI, the mach

safetyarxiv-cs-ai

Color Independent Word Segmentation From Transcribed Bangla Passages

arXiv:2610.01191v1 Announce Type: new Abstract: An optical character recognition(OCR) system can scan paper and extract text, making people's jobs easier. While numerous OCR systems are accessible in

researcharxiv-cs-cv

CompMat-Bench: Benchmarking AI Agents for Computational Materials Science

arXiv:2610.00636v1 Announce Type: new Abstract: Evaluating AI agents on scientific research tasks is constrained by the time and resources required for the underlying experiments or calculations. In c

FastCI: Efficient GPU-Intensive CI for LLM Training Frameworks

arXiv:2610.01967v1 Announce Type: new Abstract: As large language models (LLMs) keep growing in size and complexity, their training frameworks evolve at a rapid pace as well. Therefore, continuous int

hardwarearxiv-cs-lg

Finding the Right Fit: Model-Harness Interactions across Agent Tasks

arXiv: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

Generalized Engression Models

arXiv:2610.01823v1 Announce Type: cross Abstract: We consider estimating the conditional distribution of a multivariate outcome given covariates when its coordinates may be continuous, binary, categor

Groundability, Not Scale Alone: When Weak Reviewers Can Audit Strong Coding Agents

arXiv: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

LLM-based Agentic Reasoning Frameworks: A Survey from Methods to Scenarios

arXiv:2508.17692v2 Announce Type: replace Abstract: Recent advances in LLM-based agents highlight the importance of their reasoning frameworks, which guide the problem-solving process in diverse ways.

Open Vocabulary Word Recognition From Transcribed Bangla Texts

arXiv:2610.01134v1 Announce Type: new Abstract: An optical character recognition (OCR) can scan a paper and extract text using technology, making people's jobs easier. While various OCR systems are av

researcharxiv-cs-cv

TRACE: Tackling Real-World Resource Assignment Problems via Agentic Heuristic Design

arXiv:2610.01887v1 Announce Type: cross Abstract: Dynamic resource assignment, the real-time allocation of task streams to heterogeneous processing nodes, is the backbone of modern computing infrastru

Community-Driven API and AI Writer Design for Openly Scaling Community Notes

arXiv:2609.40067v1 Announce Type: cross Abstract: Community Notes is a crowd-sourced approach for adding context to posts on X. Contributors propose and rate notes, forming the inputs to an open-sourc

CompoWorld: Compositional Environment Scaling for General Agents

arXiv:2609.33665v2 Announce Type: replace Abstract: Automatically generated environments provide a scalable source of interaction data for training general agents. However, existing approaches mainly

DoGBench: Can Agents Meet Expert Standards for User-Facing Documentation?

arXiv:2609.39909v1 Announce Type: cross Abstract: We introduce DoGBENCH (Documentation Generation Benchmark), to our knowledge, the first benchmark for generating and maintaining real user-facing soft

From Verification Failures to Reusable Guidance for Coding Agents

arXiv:2609.39022v1 Announce Type: cross Abstract: Coding agents need to establish that a program satisfies a specification and that the specification captures the requested behavior. We study how expe

Learning from Research: Toward Lifelong Agent Harness Evolution

arXiv: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

Learning When and How to Intervene: A Hindsight-Distilled Sentinel for Coding Agents

arXiv:2609.39957v1 Announce Type: cross Abstract: Coding agents solve repository-level tasks through sequences of actions, where a single erroneous action can misdirect subsequent decisions and increa

MiniRep: Robust Reputation-Based Aggregation for Multi-Agent Debate

arXiv:2609.39297v1 Announce Type: new Abstract: Autonomous agents powered by large language models (LLMs) are rapidly evolving into an open agentic ecosystem. To support trustworthy collaboration, ind

PivotOPD: Learning to Recover from Pivotal Mistakes in Multi-Turn Agents

arXiv: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

RefCon: Iterative Refinement and Contrastive Memory Extraction for Context-Evolving Agent

arXiv:2609.39143v1 Announce Type: new Abstract: Long-horizon agent interactions generate useful but noisy experience, and retraining models to absorb it is expensive. Context-evolving agents therefore

Representation Risk in Pretrained Image Encoders

model-releasesarxiv-cs-cv

arXiv:2609.35470v1 Announce Type: cross Abstract: Applied researchers increasingly convert images into features with pretrained encoders, then use those features in a downstream prediction model. The

The Nixtlaverse: An Open-Source Ecosystem for Forecasting

arXiv:2609.39741v1 Announce Type: new Abstract: Large forecasting applications often combine statistical, machine-learning, and neural models. These families solve the same problem but differ in fitte

Local Ai

Towards Model as a Library: Offline, Community-Sourced AI for Low-Resource African Languages

arXiv:2609.38574v1 Announce Type: new Abstract: Large language models are frequently proposed as a route to AI-powered services for African communities, but they are least reliable exactly where the n

local-aiarxiv-cs-ai

Turbo Harness: Instance-Adaptive Harness Optimization

arXiv:2609.40330v1 Announce Type: new Abstract: Automating the search for effective harnesses is an important step toward enabling agents to recursively self-improve. Existing harness optimizations ty

AI as a Compiler: Compiling Triton kernels without the Triton compiler

arXiv: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

hardwarearxiv-cs-ai

Tutorials

Benchmarking graph-based models for in-silico toxicity prediction in drug discovery

arXiv:2609.37555v1 Announce Type: new Abstract: Drug discovery is a costly and high-risk process, where toxicity-related failures remain a major cause of attrition in both preclinical and clinical sta

tutorialsarxiv-cs-lg

Can Language Models Learn to Forecast Stock Prices

model-releasesarxiv-cs-cl

arXiv:2609.36914v1 Announce Type: new Abstract: Post-training has been shown to significantly improve language models' performance on tasks with verifiable outcomes, including mathematical reasoning,

Applications

DQ-MPCC: Dual-Quaternion MPCC for Quadrotor Racing

arXiv:2609.36482v1 Announce Type: new Abstract: Quadrotor racing demands aggressive attitude and progress control while passing through every gate, and conventional quadrotor MPCC formulations state t

applicationsarxiv-cs-ro

Evaluating System One Models for Agent Security Decisions: Reliability, Calibration, and Selective Automation

arXiv:2609.33401v2 Announce Type: replace-cross Abstract: Model-based judges support agent security by detecting prompt injections, assessing interaction risks, and screening harmful requests. System

Applications

How Much Prompt Is Enough? A Blackbox Minimization of Few-Shots in LLMs

arXiv:2609.36289v1 Announce Type: cross Abstract: Prompts are the primary mechanism for directing the behavior of large language models (LLMs). Yet the internal structure and causal hierarchy of promp

applicationsarxiv-cs-ai

Learning Nonlinear Finite Element Solution Operators using Multilayer Perceptrons and Energy Minimization

arXiv:2412.04596v3 Announce Type: replace Abstract: We develop and evaluate a method for learning solution operators to nonlinear problems governed by partial differential equations (PDEs). The approa

researcharxiv-cs-lg

Tutorials

Mubric: Mutation Testing-Guided Rubric Generation for LLM Evaluation

arXiv:2609.37322v1 Announce Type: new Abstract: Rubric-based evaluation is widely used to assess LLM-based systems by decomposing response quality into task-specific scoring criteria. However, automat

tutorialsarxiv-cs-ai

Recompositional Robotics: Cross-Domain, Open-set, and Lifelong Modularity Beyond Morphology

arXiv:2609.37734v1 Announce Type: new Abstract: Research in modular robotics has produced capable approaches allowing a robot's morphology to change online, with recent efforts also developing approac

researcharxiv-cs-ro

Relic: From Multi-Agent Collaboration to Persistent Organizational Capability

arXiv:2609.32965v2 Announce Type: replace Abstract: Multiple agents may often conflict in an organization: for example, one coding agent changes an interface in a repository, but another continues to

ROSS: Relearning from Self-Generated Rollouts through Selective Supervision

arXiv:2609.35954v1 Announce Type: cross Abstract: Large language model post-training generates self-generated rollouts through reinforcement learning and on-policy distillation, yet this experience is

Tutorials

The Uneven Decline of Collective Knowledge Production: Evidence from Stack Overflow After Generative AI

arXiv: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

tutorialsarxiv-cs-ai

Accelerator Choice Is Not Enough: AlphaFold2 Inference on Cloud TPUs

arXiv: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

hardwarearxiv-cs-lg

Safety

Certified Multi-Source Integrity for Structured Agent Actions

arXiv:2609.34245v1 Announce Type: cross Abstract: LLM agents increasingly take privileged, often irreversible structured actions, such as paying an invoice. They assemble each action from action-criti

safetyarxiv-cs-lg

Fast and Precise Learned Charged-Particle Trajectory Regression at the Large Hadron Collider

arXiv:2609.32479v1 Announce Type: new Abstract: We propose a training recipe that treats charged-particle trajectory parameter regression on high-energy physics detector data as a sequence-modeling ta

Greenpixie's AI Token Methodology: Assessing the Energy, Water and CO_2ext{-eq} Impact of AI Tokens for Open and Closed Weight Models

arXiv:2609.33965v1 Announce Type: cross Abstract: We describe a methodology for estimating the per-token energy cost of cloud-hosted large language model (LLM) inference, separating between input (pre

hardwarearxiv-cs-lg

ROTE: Benchmarking Neural Memorization on Complexity-Controlled Symbolic Sequences

arXiv:2609.31918v1 Announce Type: new Abstract: We introduce ROTE (RollOut Testing of Exact memorization), a benchmarking protocol for evaluating symbolic memorization of neural architectures. We stud

Sparsity by Default: The Theory and Practice of ARD in Gaussian Process Regression for Variable Selection

arXiv:2609.33550v1 Announce Type: cross Abstract: Automatic relevance determination (ARD) is the standard device for input selection in Gaussian process (GP) regression. By giving the covariance kerne

researcharxiv-cs-lg