Search: “llm”

Intent Engine: Natural-Language Intent Translation for Intent-Driven Orchestration in the Compute Continuum

arXiv:2608.20388v1 Announce Type: new Abstract: Microservice placement in the compute continuum is driven by low-level Service-level Objectives (SLOs), but requiring users to specify metric-level cons

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Model Releases

Large Language Models at the Intersection of Software Engineering and Software Security:An Evidence-Centered Structured Survey and Research Agenda

DGX agent

arXiv:2608.21107v1 Announce Type: new Abstract: Large Language Models (LLMs) are moving from code completion toward repository-scale agents that retrieve context, edit files, execute tools, and partic

model-releasesarxiv-cs-ai

24 Aug 2026

Structure for Reading, Prose for Writing: Asymmetric Structural Conditioning in Multi-Agent Document Authoring

arXiv:2608.20786v1 Announce Type: new Abstract: Multi-agent pipelines that author formal documents must both read a requester's forms and write against them. We report a deployed tender-response syste

Applications

StruProKGR: A Structural and Probabilistic Framework for Sparse Knowledge Graph Reasoning

arXiv:2512.12613v2 Announce Type: replace Abstract: Sparse Knowledge Graphs (KGs) are commonly encountered in real-world applications, where knowledge is often incomplete or limited. Sparse KG reasoni

applicationsarxiv-cs-cl

Hardware

Valid Inference with Synthetic Data via Task Exchangeability

arXiv:2606.13629v2 Announce Type: replace-cross Abstract: There is a proliferation of work arguing for the use of synthetic data in scientific research. For example, social scientists are arguing for

hardwarearxiv-cs-ai

When Words Are Safe But Actions Kill: Probing Physical Jailbreak Beyond Textual Jailbreak in Hidden-State Risk Space

arXiv:2607.15218v2 Announce Type: replace Abstract: Large language models (LLMs) increasingly serve as high-level planners for embodied agents, where linguistically benign instructions can become unsa

Lightweight agent to use on laptop?

Hi there. I have a Lenovo Yoga laptop (16GB LPDDR5, AMD Ryzen 7 8840HS, integrated GPU). I have downloaded Ollama and installed Qwen 2.5coder:3b llm. I have tried OpenClaw, and Qwen Code but it seems

model-releasesr-ollama

22 Aug 2026

Research

Forking Fast: Efficiently Estimating Uncertainty Dynamics in Text Generation

arXiv:2608.19611v1 Announce Type: cross Abstract: LLM reasoning is stochastic, and so understanding a model requires grappling with the distribution of reasoning chains that it might produce for a giv

researcharxiv-cs-ai

Pandora's AI Model Routing Box: Efficient Allocation with Costly Value Estimation

arXiv:2608.20316v1 Announce Type: new Abstract: Heterogeneous AI systems composed of multiple models, architectures, harnesses, or inference-time settings can improve quality and efficiency by routing

Scale-Aware Pretraining of Time Series Foundation Models via Multi-Patch Token Alignment and Hybrid Masking

arXiv:2608.20005v1 Announce Type: new Abstract: Pretraining time series foundation models across heterogeneous datasets necessitates effective handling of varying sampling frequencies. Current methods

safetyarxiv-cs-lg

Research

Towards Audio Token Compression in Large Audio Language Models

arXiv:2511.20973v2 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) deliver strong performance across speech and audio tasks, but their audio encoders generate high-rate toke

researcharxiv-cs-ai

Tutorials

What You Can't See Is What You Learn: Restricted Evidence Visibility Favors Compositional Generalization in Shared-Genome Language-Model Societies

arXiv:2608.20054v1 Announce Type: new Abstract: Multi-module systems often expose every module to the full input. We test whether restricting evidence visibility changes which solutions gradient-based

tutorialsarxiv-cs-ai

DigitalOcean Inference Router, Now Cache-Aware: Why the Cheapest Model Isn't Always the Best Deal

model-releasesdigitalocean

Coinbase CEO Brian Armstrong recently posed the question every company scaling AI is asking: how do you keep spend flat while token usage grows exponentially? This isn’t hypothetical. It’s confronting

FraudBench: Stress-Testing Policy-Grounded Banking Agents Against Adaptive Fraud

arXiv:2608.18136v1 Announce Type: new Abstract: Conversational agents now act for end users through tools while holding access to customer databases and internal policy documents that a caller can rea

Research

Hallucination Detection in Large Language Models Using Diversion Decoding

arXiv:2607.10476v2 Announce Type: replace Abstract: Large language models (LLMs) have emerged as a powerful tool for retrieving knowledge through seamless, human-like interactions. Despite their advan

researcharxiv-cs-cl

Institutional Prestige as Geographic Bias in Large Language Models: Evidence from Three Factorial Experiments with Bootstrap Confidence Intervals

arXiv:2608.18107v1 Announce Type: cross Abstract: We investigate whether large language models (LLMs) systematically discriminate in candidate evaluations based on applicant name ethnicity and/or inst

SkillGate: Training In-Policy Skill Selection in Long-Horizon Agents

arXiv:2608.18852v1 Announce Type: new Abstract: Agent frameworks increasingly package procedural knowledge as skills: instruction files an agent reads on demand, while public libraries now hold thousa

StocksTalk: A Voice-Enabled Conversational Agent for Structured Query Generation over Web Data

arXiv:2608.18105v1 Announce Type: cross Abstract: StocksTalk is a voice-enabled conversational system for transforming spoken financial screening requests into executable and validated structured quer

Agent Lightning v1.0: Towards Harnessed Agentic RL

arXiv:2608.17528v1 Announce Type: new Abstract: Modern agents operate inside agent harnesses that manage tools, context, and control flow, making the harness a critical part of the agent system. Our o

CABLE: Extending the Reach of Memory Retrieval via Complementary Antecedent-Based Linking and Expansion

arXiv:2608.17911v1 Announce Type: new Abstract: As LLM agents operate across structured workflows and sessions, preserving long-term history does not ensure that later contexts can recover relevant ev

DataSTORM: Deep Research on Large-Scale Databases using Exploratory Data Analysis and Data Storytelling

arXiv:2604.06474v2 Announce Type: replace Abstract: Deep research with Large Language Model (LLM) agents is emerging as a powerful paradigm for multi-step information discovery, synthesis, and analysi

agentsarxiv-cs-cl

Effects of Answer Format Variation on Gender Bias in Large Language Models

arXiv:2608.17516v1 Announce Type: new Abstract: Gender bias or other social biases in large language models (LLMs) are frequently evaluated with question answering or survey benchmarks where the LLM n

Fair ASR: Re-Evaluating Black-Box Jailbreaks under Shared Target-Call Budgets

arXiv:2608.17360v1 Announce Type: cross Abstract: Reliable jailbreak evaluation is essential for assessing LLM safety, but most existing studies rely solely on attack success rate (ASR) without accoun

MobileWorldSafety: Benchmarking GUI Agent Safety Against Environmental Injection Attacks in Android Apps

arXiv:2608.17659v1 Announce Type: cross Abstract: LLM-powered GUI agents that autonomously operate smartphones are rapidly transitioning from research prototypes to early real-world deployment. Howeve

On the Fragility of Self-Improving Agents: Variance, Task Order, and Underspecification

arXiv:2608.18066v1 Announce Type: new Abstract: Memory-based self-improving agents--those that learn from an online stream of tasks and improve over time by maintaining a textual memory bank--have sho

PACE: Policy-Attested Contract Execution for Safe AI Agents in Decentralized Finance

arXiv:2608.17220v1 Announce Type: cross Abstract: Autonomous AI agents are emerging as interfaces for decentralized finance (DeFi) actions such as swaps, lending operations, and yield management. Beca

PrivAct: Internalizing Contextual Privacy Preservation via Multi-Agent Preference Training

arXiv:2602.13840v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly deployed in personalized tasks involving sensitive, context-dependent information, where privacy

agentsarxiv-cs-cl

Runtime Governance for Agentic AI: Action-Boundary Control with Trusted Provenance and Fail-Closed Execution

arXiv:2608.16891v1 Announce Type: new Abstract: Agentic AI systems request tool actions that can modify files, send messages, launch jobs, or change workflow state. This shifts the safety problem from

TRUSS: Towards Task-Reliable and User-Safe Automated Agent Skill Generation

arXiv:2608.17588v1 Announce Type: new Abstract: Agent Skills package reusable natural language procedures with executable resources, enabling software agents to acquire task specific capabilities with

Local Ai

Waiting for a 122B because of world knowledge?

Any LLM will hallucinate the world knowledge, even a 3T model. Use a 4B with a kiwix skill and local Wikipedia, 50gb and no more hallucinated world knowledge. Ask your coding agent to build your own,

local-air-localllama

When Agents Act on Web3: An Attack-Surface Survey of MCP, Skills, and Tool Calling

arXiv:2608.17275v1 Announce Type: cross Abstract: AI agents increasingly act rather than merely read: across the Model Context Protocol (MCP) ecosystem, the share of deployed tools that modify externa

AutoMem: A Text-Gradient Recursive Self-Improvement Framework for Automated Memory Architectures Search

arXiv:2608.14621v1 Announce Type: cross Abstract: Long-term memory is increasingly central to LLM agents, yet memory design remains a highly coupled architecture problem: what to encode, how to store

Dense Expands, Sparse Anchors: Channel-Asymmetric Query Expansion for Hybrid Retrieval

arXiv:2608.15851v1 Announce Type: cross Abstract: LLM-based query expansion improves retrieval by generating document-like passages. In hybrid retrieval, however, most evaluations fuse fixed top-L den

safetyarxiv-cs-cl

Divergent-Convergent Reasoning: Scaling Test-Time Compute through Structured Solution Synthesis

arXiv:2608.15303v1 Announce Type: new Abstract: Test-time compute can substantially improve Large Language Model (LLM) reasoning performance, yet how and when additional compute helps remains poorly u

Evaluating Agentic Code Repair Capabilities in Distributed Systems

arXiv:2608.14863v1 Announce Type: cross Abstract: LLM-based coding agents have advanced rapidly on single-process SWE tasks, with frontier models now clustering in the high-70s on SWE-bench Verified.

Evo-Harness: Context-to-Harness Skill Compilation for Self-Evolving Agents

arXiv:2608.15071v1 Announce Type: new Abstract: Learning from experience is critical for developing capable, self-improving large language model (LLM) agents. Existing methods typically extract knowle

Harness the Memory: A Holistic Evaluation of Memory Substrates in Memory Agents

arXiv:2608.15008v1 Announce Type: new Abstract: Memory is becoming core infrastructure for long-horizon LLM agents, yet existing evaluations offer limited guidance on which memory substrate, namely th

Hierarchical Agentic Incident Response with Digital-Twin-Validated Attack Inference

arXiv:2608.15016v1 Announce Type: cross Abstract: Network incident response remains slow and labor-intensive as the defender must infer multi-stage attacks from partial observations and translate reco

Local Ai

LENS: In-Context Search via Latent Evidence Exploration over Dynamic Raw Documents

arXiv:2608.16185v1 Announce Type: cross Abstract: LLM agents increasingly answer questions over dynamic raw-document collections, where files may change before preprocessing, and relevant evidence (sp

local-aiarxiv-cs-ai

Reasoning-Based Personalized Generation for Users with Sparse Data

arXiv:2602.21219v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) personalization holds great promise for tailoring responses by leveraging personal context and history. However, re

TAHB: A Comprehensive Benchmark for Text-Attributed Hypergraph Learning

arXiv:2608.15055v1 Announce Type: new Abstract: Hypergraphs effectively model higher-order groupwise relationships beyond pairwise interactions, while pretrained language models (PLMs) and large langu

Walk Before You Run: The Importance of Data Exploration for Data Analysis Agents

arXiv:2608.16045v1 Announce Type: cross Abstract: LLM-based data-analysis tools are increasingly used to help users analyze messy spreadsheets and workbooks, from answering questions over uploaded fil

Demystifying Agent Skills: Why They Work-Until They Don't

arXiv:2608.14036v1 Announce Type: new Abstract: Skills have emerged as a practical and effective approach for enhancing LLM agents at inference time through structured packages of knowledge. However,

Handover of In-Context Learning State Across Session Boundaries

arXiv:2608.14528v1 Announce Type: new Abstract: This study investigates the methodological and theoretical properties of session handover in applications that use large language models. A task may con

Measuring Cross-Task Behavioral Consistency in Language Model Agents

arXiv:2608.13598v1 Announce Type: new Abstract: Agent evaluation relies almost entirely on outcome metrics such as success rate, which capture whether an agent succeeds but not how consistently it beh

Never the Number: Structural Abstention for AI Systems Whose Answers Are Consumed as Fact

arXiv:2608.13926v1 Announce Type: new Abstract: Large language models have made natural language interfaces to databases (NLIDB) newly credible, but LLM text-to-SQL systems fail in a way that matters

ScienceFlow: A long-horizon agent for ML research, scientific discovery and beyond

arXiv:2608.14354v1 Announce Type: new Abstract: Enabling LLM agents to sustain productive, stable, and goal-aligned research over extended horizons is a central challenge for autonomous machine learni

Understanding and Mitigating Over-refusal for Large Language Models via Representation Intervention

arXiv:2511.19009v2 Announce Type: replace-cross Abstract: Large language models (LLMs) demonstrate powerful capabilities across various natural language processing tasks,yet their inherent safety vuln

safetyarxiv-cs-cl