Search: “llm”

GraphSkillEvo: Evolutionary Optimization of Graph-Structured Agent Skills

model-releasesarxiv-cs-lg

arXiv:2609.21749v1 Announce Type: new Abstract: Skills can improve the performance of Large Language Model (LLM) agents by providing task-specific procedural guidance, while skill optimization further

21 Sept 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Predictable Failure in Multi-Hop Retrieval: Score-Distributional Confidence Scoring and Abstention

DGX agent

arXiv:2609.22056v1 Announce Type: cross Abstract: Multi-hop retrieval failures are not uniformly distributed across queries: they cluster in structurally predictable subpopulations. We prove two resul

safetyarxiv-cs-cl

21 Sept 2026

Been integrating Jev into my custom harness. I couldn't be more excited about the results I am seeing. Most demos on my timeline are flashy …

Been integrating Jev into my custom harness. I couldn't be more excited about the results I am seeing. Most demos on my timeline are flashy but very basic. Notice they are all about some boring classi

agentsdair-ai--x

19 Sept 2026

Amazon SageMaker Inference: 2026 year-to-date launches in review

model-releasesaws-ml-blog

Amazon SageMaker AI shipped 13 inference launches in the first half of 2026 across two deployment paths: fully managed endpoints and Amazon SageMaker HyperPod Inference. This post reviews each launch,

I stopped using the smartest AI models. Programming got faster and cheaper.

Vacations give you time to think and explore. I came across a few things and made a few discoveries of my own. It turns out that, as a programmer, I no longer need the smartest and most expensive AI m

model-releasesr-ollama

Large Language Models as Falsifiers for Cyber-Physical Systems

arXiv:2609.20752v1 Announce Type: cross Abstract: Falsification searches for counterexamples to formal specifications in cyber-physical systems (CPS). With specifications written in Signal Temporal Lo

MAGS: Multi-agent Auto-formalization Guarantees Safety for Agentic Outputs

arXiv:2609.19391v1 Announce Type: new Abstract: LLM coding agents now generate complex programs at a scale that makes thorough human review increasingly difficult, raising the risk of safety and secur

Message capacity and claim wording set the transition points of collective truth-finding in language-model networks

arXiv:2609.19183v1 Announce Type: cross Abstract: Whether human or large language model (LLM), an agent in a discussion reads only a few of the others' contributions, bounded by cognition, context, or

Q&A on Any Spreadsheet Requires Interpreting Its Grid Structure

arXiv:2609.20732v1 Announce Type: new Abstract: Semantic cell annotation improves chunking interpretability for spreadsheets in LLM-driven RAG systems, aiding answer generation through enriched contex

REARL: A Closed-loop Autonomous Driving Simulation Enhancement Framework with Real Traffic Data and Large Language Models

arXiv:2609.19903v1 Announce Type: new Abstract: Accurate simulation is crucial for autonomous driving development, yet capturing real-world traffic complexity remains challenging. Existing simulators

agentsarxiv-cs-lg

To Copy or Not to Copy: Controlling Speculative Decoding via Intrinsic Model Signals

arXiv:2609.20186v1 Announce Type: new Abstract: Speculative Decoding (SD) has significantly accelerated Large Language Model (LLM) inference, yet existing approaches face a fundamental tradeoff betwee

Local Ai

Understanding and Exploiting Diagonal Attention Sparsity in Autoregressive Image Generation

arXiv:2609.19702v1 Announce Type: new Abstract: Autoregressive image generation has emerged as a paradigm for multimodal AI systems due to its compatibility with transformer-based LLM serving infrastr

local-aiarxiv-cs-cv

Autonomy in Check: Governor-Mediated Adaptive Security at the Edge

arXiv:2609.18338v1 Announce Type: cross Abstract: Adaptive security at the network edge increasingly relies on automated planners, including rule-based controllers, learned policies, and LLM-assisted

Correlation-Guided Encoder Selection for Multi-Encoder Large Audio-Language Models

arXiv:2609.18041v1 Announce Type: cross Abstract: Multi-encoder fusion extends Large Audio-Language Models (LALMs) beyond speech-centric recognition, but selecting encoders via intuition or exhaustive

Designing Agentic AI Workflow Portfolios under Imperfect Selection and Compute Cost

arXiv:2609.18126v1 Announce Type: new Abstract: Agentic AI systems often approach the same task through multiple workflows that differ in reasoning strategy, verification structure, and compute cost.

Applications

Emotion Experience, Expression, and Perception: Emotion Analysis on Multimodal Social Media Posts

arXiv:2609.18385v1 Announce Type: new Abstract: Emotions are an essential aspect of human communication, particularly on social media, where authors frequently combine text and images to convey their

applicationsarxiv-cs-cl

GYROval: A Robust Benchmark for Cultural Value Orientation in Large Language Models

arXiv:2609.18384v1 Announce Type: cross Abstract: We present a robust benchmark for measuring cultural value orientation in large language models on the two Inglehart-Welzel axes over several domains

How AI Assistants Respond to Repeated Abuse

arXiv:2609.17547v1 Announce Type: new Abstract: AI assistants are expected to remain useful during difficult interactions, but little is known about how repeated verbal abuse changes their engagement

Hyperbolic Graph Representation Learning for Differential Diagnosis on Biomedical Knowledge Graphs

arXiv:2609.18481v1 Announce Type: new Abstract: Biomedical knowledge graphs combine ontology-derived hierarchies with transversal associations among heterogeneous entities such as phenotypes, diseases

Lexara-RF: Reference-Free Metrics for Evaluating Conversational Visual Analytics Agents

arXiv:2609.17842v1 Announce Type: cross Abstract: Conversational visual analytics (CVA) agents powered by large language models generate visualizations and natural-language explanations from open-ende

M-SQE: Multilingual Skill Quality Estimation for Enhancing Language Equality in Agentic Skill Use

arXiv:2609.18445v1 Announce Type: new Abstract: Agent skills, reusable procedural documents that extend LLM agents beyond their parametric memory, have become an important interface for deploying agen

agentsarxiv-cs-cl

Reflect, Revise, Reuse: Training-Free Skill Evolution for GUI Agents

arXiv:2609.17653v1 Announce Type: cross Abstract: GUI agents execute long-horizon tasks on dynamic graphical user interfaces, where pop-ups, delayed loads, and relocated widgets routinely invalidate p

Applications

SAGE: Governed Artifact Generation from Enterprise Guidelines

arXiv:2609.17775v1 Announce Type: new Abstract: Enterprise guideline documents mix narrative text, complex tables, and embedded images, and converting them into structured work artifacts still takes t

applicationsarxiv-cs-ai

Schmidhuber was building recursive self-improving systems back in 1987. His new post covers four decades of RSI, from meta-evolution and sel…

Schmidhuber was building recursive self-improving systems back in 1987. His new post covers four decades of RSI, from meta-evolution and self-modifying policies to the Gödel Machine and modern LLM age

safetydavid-ha--x

Self-generated prompt injections in compaction summaries

model-releasessimon-willison

Self-generated prompt injections in compaction summaries In Our framework for reporting model misalignment OpenAI provide 'six reports on unexpected or concerning model behavior we’ve observed in the

StableEval Arena: A Cost-Aware Agentic Benchmark for Stablecoin Price Stability Prediction

arXiv:2609.18949v1 Announce Type: cross Abstract: We introduce StableEval Arena, a cost-aware benchmark framework for evaluating agentic AI systems on stablecoin peg-risk prediction. StableEval Arena

The Missing 'I Don't Know': Why Three Reasoning-Reliability Findings Converge on Calibrated Abstention

arXiv:2609.17686v1 Announce Type: cross Abstract: Three recent results describe what look like unrelated LLM reliability problems. Yin et al. (2026) show reasoning RL collapses tool-reliability repres

A Framework for Generating Valid Context-Specific Benchmarks through Expert Guidance

arXiv:2609.16592v1 Announce Type: new Abstract: This paper presents an end-to-end approach for generating context-specific large language model (LLM) benchmark datasets by combining expert input with

Agentic Search Spaces for Tabular Machine Learning

model-releasesarxiv-cs-lg

arXiv:2609.16309v1 Announce Type: new Abstract: Despite the rapid progress of LLM-based agents for planning, code generation, and debugging, their practical value for tabular machine learning remains

AI Policies: Help or Hindrance? A Software Developer's Perspective

arXiv:2609.16496v1 Announce Type: cross Abstract: AI policies introduced by software organisations to mitigate LLM-related risks such as sensitive information leaks and unauthorised usage are not usef

b11003

model-releasesllama-cpp-releases

model : add support for HrmTextForCausalLM (DFM Mimir 1B) (#27625) model : add support for HrmTextForCausalLM (DFM Mimir 1B) HRM-Text runs two transformer stacks (low, high) in an alternating cycle ov

Coaching Qwen3 Coder 30B to Think Like a CodeClash Arena Agent

arXiv:2609.16096v1 Announce Type: cross Abstract: Large language model coding agents have recently become useful for software tasks, but weaker or open-weight agents still struggle to reliably interpr

ECHO: Early-layer Collaborative Hierarchical Orchestration with Bonus Logits in Speculative Decoding

arXiv:2609.17241v1 Announce Type: new Abstract: While draft-model-free speculative decoding offers a promising path to efficient LLM inference, it is frequently constrained by stale draft candidates a

researcharxiv-cs-cl

Never Stop Thinking: Continuous-Time Language Agents

arXiv:2609.17416v1 Announce Type: new Abstract: Voice agents built on LLMs follow a rigid listen-think-speak loop that inserts seconds of dead air before every reply. We show that continuous-time cogn

Protocol-Preserving Context Trimming for Agentic Workflows: Benefits, Failure Regimes, and Budget Guardrails

arXiv:2609.16461v1 Announce Type: cross Abstract: Agentic large language model (LLM) systems rely on long interaction histories to preserve instructions, tool states, intermediate decisions, and unres

QART: A Quantum-Classical Hybrid Architecture for Long-Horizon Reasoning -- Exploring a Conditional Path toward Quantum Scaling

arXiv:2609.16887v1 Announce Type: new Abstract: Long-horizon reasoning is vulnerable to early errors that compromise later decisions. We present QART, the Quantum-Augmented Reasoning Transformer, a qu

Same Problem, Different Field: Cross-Domain Solution Import via Domain-Stripped Computational Fingerprints

arXiv:2609.07595v2 Announce Type: replace-cross Abstract: The same underlying computational problem is solved across unrelated fields under different names: recursive Bayesian state estimation appears

Self-reported archetypes and behavioral failures in Large Language Models

arXiv:2609.15998v1 Announce Type: new Abstract: Every large language model (LLM) has behavioral traits and moral preferences that comprise its character. Whether by design or as an emergent property o

Shuttling Compiler for Trapped-Ion Quantum Computers Based on Fine-Tuned Large Language Models

arXiv:2512.18021v4 Announce Type: replace-cross Abstract: In trapped-ion quantum computers, qubits must be shuttled between segments to interact. The routing logic that schedules these movements is wr

researcharxiv-cs-lg

Towards Illusions Awareness in Cyber-Physical System's Design

arXiv:2609.17260v1 Announce Type: new Abstract: Cyber-Physical Systems (CPS) operate through a continuous sense-compute-act loop within an open context environment, making it impossible to anticipate

researcharxiv-cs-cl

Where Post-Training Quantization Breaks Text Embedders: A Measured Map Across Four Embedder Families

arXiv:2609.16391v1 Announce Type: cross Abstract: Weight-only post-training quantization is the cheapest way to shrink a retrieval embedder, and the received advice for applying it -- protect the embe

researcharxiv-cs-cl

Where Should the KV Cache Live? Placement Policies Across GPU, CPU, and SSD for Long-Lived Sessions

arXiv:2609.16215v1 Announce Type: new Abstract: GPU high bandwidth memory is scarce and expensive, and KV caches consume much of it as chats, agent loops, and document question answering accumulate st

An Incomplete Loop: Deductive, Inductive, and Abductive Reasoning in Language Models

arXiv:2404.03028v4 Announce Type: replace Abstract: Modern language models (LMs) can learn to perform new tasks in different ways: in instruction following, the target task is described explicitly in

AppliedScientist: Automated Scientific Revision Through Iterative AI Reviewing

arXiv:2609.14738v1 Announce Type: new Abstract: Automated reviewing systems are increasingly evaluated based on the quality of the reviews they produce. Yet a review is only useful if acting on it lea

Asclepius: An Adaptive Harness for Long-Horizon Clinical Agents

arXiv:2609.13543v1 Announce Type: new Abstract: LLM agents are predominantly benchmarked on short, single-task trajectories, yet real deployments run for hours under contention, surfacing a different

Beyond AI Literacy: A Structured Review and Exploratory Meta-Analysis of Measures for Competent Generative-AI Use

arXiv:2609.15624v1 Announce Type: cross Abstract: Researchers assessing competent generative-AI use at work must choose among self-reports, objective tests, and measures of oversight and reliance. We

Can We Stop Malicious AI? KILLBENCH: A Benchmark for External AI Kill Switch Feasibility

arXiv:2511.13725v5 Announce Type: replace-cross Abstract: Malicious AI causing harm to humans is not just a Hollywood fantasy. Indeed, as highly capable models such as Claude Mythos emerge and agent s

ClinAgent: A ReAct-Based Agent for Conversational Access to Clinical Trial Information

arXiv:2609.13860v1 Announce Type: new Abstract: Querying clinical trial registries remains a manual and error-prone process, requiring researchers to navigate large volumes of semi-structured data wit