Search: “persistence”

Adapting Vision-Language-Action Models to Unknown Visual Disruptions During Execution

arXiv:2610.07946v1 Announce Type: cross Abstract: Visual disruptions can arise while a robot is executing a task, leaving a vision-language-action (VLA) policy to respond without knowing the disruptio

safetyarxiv-cs-ai

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Model Releases

Agent-to-agent communication with a personal agent on top is wild. Wow. I underestimated how well models like Opus 5.5 can coordinate alread…

DGX agent

Agent-to-agent communication with a personal agent on top is wild. Wow. I underestimated how well models like Opus 5.5 can coordinate already. This opens a whole new set of experiences with agents. Bu

model-releasesdair-ai--x

7 Oct 2026

Asymptotic Analysis of Empirical Risk Minimization on Entry-wise i.i.d. Heavy-Tailed Data

arXiv:2610.07637v1 Announce Type: cross Abstract: Many real-world datasets exhibit unusually large values far more frequently than predicted by Gaussian models. Heavy-tailed distributions capture this

AttSVD:Prompt-Adaptive Low-Rank KV Cache Compression via Attention-Guided SVD

arXiv:2610.06927v1 Announce Type: cross Abstract: The key-value (KV) cache of autoregressive transformers grows linearly with context length and dominates memory at long context. Most training-free re

b11474

model-releasesllama-cpp-releases

feat: add GLM5Next MTP, optimize (#29928) llama : add GLM5-Next NextN (MTP) graph Build the GLM5-Next multi-token-prediction head as graph_mtp: the NextN block embeds enorm(tok)+hnorm(h) through eh_pr

Continuous Memory Machines

arXiv:2610.07907v1 Announce Type: new Abstract: Recurrent neural networks typically compress information into a single vector-valued recurrent state, forcing short-term computation and long-term reten

Defense-in-Depth for LLMs: Evaluating Memory Gates Against Activation-Induced and Memory-Induced Sycophancy

arXiv:2610.07403v1 Announce Type: new Abstract: Long-term memory allows Large Language Models (LLMs) to maintain personalized context across interactions, but retrieved user history can induce memory-

DIPrune: Task-Aware Token Pruning with Dual Importance for Efficient Multimodal Language Models

model-releasesarxiv-cs-cv

arXiv:2610.08341v1 Announce Type: new Abstract: Recent training-free pruning approaches for Multimodal Large Language Models (MLLMs) effectively cut computational overhead by exploiting visual redunda

Tutorials

Do Neural PDE Solvers Learn the Right Dynamics?

arXiv:2610.06952v1 Announce Type: new Abstract: Neural PDE solvers can achieve low prediction errors, but do they reproduce the dynamics of the systems they model? Prediction scores alone offer an inc

tutorialsarxiv-cs-lg

Extending Music Annotation Schemas: Zero-Shot Prediction or Few-Shot Adaptation?

arXiv:2610.06920v1 Announce Type: cross Abstract: Automatic music annotation is typically tackled under the assumption of a fixed annotation schema. In practice, commercial music catalogs often need t

Fork-and-Flush: Escaping Idea Basins in Autoresearch Agents

arXiv:2610.07447v1 Announce Type: new Abstract: Autoresearch agents tackle open-ended problems by repeatedly proposing candidate solutions, evaluating them, and using feedback to guide subsequent expe

agentsarxiv-cs-lg

Harmful SFT Leaves a Continuous Trace in LLM Checkpoint Updates

arXiv:2610.07518v1 Announce Type: cross Abstract: Safety auditing of post-trained large language models typically relies on model behavior, requiring model execution and depending on the coverage of a

Tutorials

How Learning Governs Unlearning across the Memorization-Generalization Spectrum

arXiv:2610.08577v1 Announce Type: cross Abstract: While unlearning seeks to negate undesired capabilities acquired through learning, little research has examined how the way models learn shapes their

tutorialsarxiv-cs-ai

How Many Independent Samples Does a Satellite Image Contain? Generalization Bounds for Spatially Dependent Data

arXiv:2610.08227v1 Announce Type: cross Abstract: Machine learning classifiers for remote sensing imagery are typically evaluated as though every pixel were an independent sample. Spatial autocorrelat

researcharxiv-cs-cv

Introducing Google Cloud’s U4 compute: Enabling ultra-low latency trading

model-releasesgoogle-cloud-ai

In capital markets, operational success is built on predictable performance and low latency, where even tiny variations in packet timing alter queue priority and trade execution. At the same time, bot

Large Language Model Orchestration under Heterogeneous Preferences via Explicit Persona Inference

arXiv:2610.07587v1 Announce Type: new Abstract: LLM orchestration investigates how an orchestrator coordinates a group of autonomous agents to achieve common goals or maximize collective welfare. The

agentsarxiv-cs-cl

Applications

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study

arXiv:2501.18158v4 Announce Type: replace-cross Abstract: Cryptocurrencies are widely used, yet current methods for analyzing transactions often rely on opaque, black-box models. While these models ma

applicationsarxiv-cs-lg

Learning to Decide, Not to Reason: Parameter-Efficient Decision Operators via Low-Rank Activation Steering

arXiv:2610.06950v1 Announce Type: cross Abstract: Injecting skills into a frozen language model currently costs a million parameters and a reinforcement-learning pipeline. We introduce method{}, a Sys

Mechanistic Interpretability of Atmospheric Rivers in GraphCast

arXiv:2610.07583v1 Announce Type: cross Abstract: While AI weather models now rival operational forecasts, how they represent the atmosphere internally remains an open question: feature attribution re

MedZERO: Self-Evolving Agents for Open-Ended Medical Reasoning Through Controlled Knowledge Accumulation

arXiv:2610.08327v1 Announce Type: new Abstract: Large language models (LLMs) have shown promise in medical question answering and clinical reasoning, yet their improvement remains constrained by stati

MiniScope: Authorizing Agents with Least-Privilege Permissions

arXiv:2512.11147v2 Announce Type: replace-cross Abstract: AI agents are increasingly granted autonomous access to sensitive user data and third-party services, making effective permission management a

Tutorials

Mu-DisCoCat: A Variational Pipeline for Compositional Generalization on Quantum Processors

arXiv:2610.08131v1 Announce Type: cross Abstract: Achieving compositional concept generalization (CoCoGen), the ability to understand novel situations by recombining learned primitives, remains a fund

tutorialsarxiv-cs-cv

Natural Language Questions as an Interface for Knowledge Graphs: QRAKEN Graph Distillation and Semantic Self-Healing

arXiv:2610.08095v1 Announce Type: new Abstract: Natural-language access to RDF knowledge graphs is a core Semantic Web ambition. Large language models (LLMs) have advanced Text-to-SPARQL, yet on unfam

OntoPlan: An Ontology-Grounded Scene Representation and Agentic Framework for Scalable Robot Task Planning

arXiv:2610.07649v1 Announce Type: new Abstract: Large language model (LLM)-based robot task planning is promising for open-ended instruction following, but degrades on long-horizon tasks in large envi

agentsarxiv-cs-ro

OOPMAS: Object-Oriented Multi-Agent Systems for Query-Level Workflow Generation

arXiv:2610.07787v1 Announce Type: new Abstract: Multi-agent systems (MAS) powered by large language models have shown strong performance across code generation, mathematical reasoning, and question an

Quantifying the Gap between Understanding and Generation within Unified Multimodal Models

model-releasesarxiv-cs-cl

arXiv:2602.02140v2 Announce Type: replace Abstract: Recent advances in unified multimodal models (UMM) have demonstrated remarkable progress in both understanding and generation tasks. However, whethe

SimCortex v2: Joint Cortical Surface Reconstruction with Near-Zero Collisions and Self-Intersections

model-releasesarxiv-cs-cv

arXiv:2610.07378v1 Announce Type: new Abstract: Reconstructing cortical WM and pial surfaces from structural magnetic resonance imaging (MRI) is a prerequisite for surface-based neuroanatomical analys

Skillful Data-Driven Subseasonal Soil Moisture Forecasting: Prospects and Limits for Flash Drought Prediction

arXiv:2610.07060v1 Announce Type: new Abstract: Despite substantial progress in short-to-medium-range weather forecasting, predicting high-impact events such as flash droughts remains a key challenge

researcharxiv-cs-lg

SoloQ: Calibration-Free Quantization for Diffusion Language Models

arXiv:2610.07121v1 Announce Type: new Abstract: Diffusion large language models dLLMs) have emerged as a promising alternative to autoregressive language models through bidirectional diffusion-based t

SPECTRUM: Proximal Spectral Modulation for Looped Self-Distillation

arXiv:2610.07237v1 Announce Type: new Abstract: A model that learns from its own outputs inherits more than their correctness: it inherits which solutions it produces. We formulate Looped Self-Distill

Stabilizing language models under continual learning via condition-anchored distillation

model-releasesarxiv-cs-cl

arXiv:2610.06940v1 Announce Type: new Abstract: Continual adaptation of language models can change their output distribution on prompts learned earlier, while retaining every old prompt-answer pair ma

STRUCTURALCOST: A controlled reading time dataset for modeling human sentence processing difficulty

arXiv:2610.08208v1 Announce Type: cross Abstract: We introduce STRUCTURALCOST, a self-paced reading dataset of 475 participants and 40,800 observations isolating the processing cost of long-distance s

Targeted search shows that random-device testing underestimates worst-case error in a simulated wave-based neural operator

arXiv:2610.07529v1 Announce Type: new Abstract: Wave-based processors promise fast, energy-efficient Fourier layers for neural operators. They are usually validated on randomly sampled devices, but us

Text2Dashboard: A Governed Agent Architecture for Natural-Language Dashboard Generation over Enterprise DataBrain

arXiv:2610.06914v1 Announce Type: new Abstract: Text2Dashboard is a DataBrain-specific prototype that turns natural-language analytic requests into inspectable dashboards. An installable Codex plugin

agentsarxiv-cs-ai

The Model Plants the Trigger: Answer-Side Backdoor Attacks in Multi-Turn Large Language Models

arXiv:2610.07723v1 Announce Type: cross Abstract: Safety alignment in Large Language Models (LLMs) remains vulnerable to backdoor attacks. Existing LLM backdoors are almost all input-centric: activati

Unanimously Wrong: Certified Abstention from How Medical LLM Consensus Forms

arXiv:2610.07570v1 Announce Type: new Abstract: In clinical practice, agreement among independent experts is treated as evidence of reliability, and multi-round consensus has become a core mechanism o

agentsarxiv-cs-ai

Which and When to Admit: Gradient Admission for Data-Centric Small Language Model Finetuning

arXiv:2610.07553v1 Announce Type: cross Abstract: LoRA fine-tuning adapts small language models (SLMs) to heterogeneous instruction data within a low-rank update subspace, making it vulnerable to thre

Who Wrote It Is Not Enough: Detecting Who Contributed the Insight

model-releasesarxiv-cs-cl

arXiv:2610.07365v1 Announce Type: new Abstract: As LLMs increasingly assist scientific writing and peer review, detecting who wrote the text is no longer sufficient: we need to determine who contribut

Hardware

Wikidata Search Traces: A Dataset for Training Knowledge Graph Search Agents

arXiv:2610.06650v2 Announce Type: replace Abstract: Wikidata is one of the largest open knowledge bases, yet answering a complex question over it still requires a SPARQL query that names the right ent

hardwarearxiv-cs-cl

World Models' Last Exam in Physics

model-releasesarxiv-cs-cv

arXiv:2610.08791v1 Announce Type: new Abstract: Video world models can produce visually convincing yet physically inconsistent sequences, raising concerns about their reliability for prediction and pl

Local Ai

A local 27B model reads my lease and finds a leak in my bills | Row-Bot + qwen3.8 on Ollama

Row-Bot 5.0 with qwen3.8:27b in Ollama, on my own GPU. No API keys, no cloud. Gave it a year of bills, a tenancy agreement, an insurance policy and a rent increase letter (all made up). It spotted a l

local-air-ollama

Adaptive Bregman Alternating Projections for Feasible Gromov-Wasserstein Learning

arXiv:2610.04264v1 Announce Type: new Abstract: The Gromov-Wasserstein (GW) problem compares structured distributions without requiring a shared feature space or known correspondences, but its nonconv

AgenticTactileVLA: Contact-Guided Execution-Time Supervision for Generalizable Dexterous Manipulation without VLA Retraining

arXiv:2610.04391v1 Announce Type: new Abstract: Vision-language-action policies may predict a transferable manipulation strategy yet fail to realize it reliably on the encountered object: objects comp

researcharxiv-cs-ro

All against the machine: the Solo score for rating skill in variable environments

arXiv:2610.04523v1 Announce Type: cross Abstract: We propose a distribution-free metric to rate individual skill in ``player-versus-environment'' settings, where participants face heterogeneous tasks

ALoDLM: Adaptively Looped Diffusion Language Models

arXiv:2610.04198v1 Announce Type: cross Abstract: Diffusion language models (DLMs) enable fast generation by predicting multiple tokens in parallel, but their practical adoption remains limited by a p

Anticipating the Consequences of Curriculum Decisions with Large Language Models

arXiv:2610.04604v1 Announce Type: new Abstract: Automatic curriculum learning can improve the effectiveness of reinforcement learning by selecting the training experiences presented to the agent over

Backdoor Attacks on Discrete Graph Diffusion Models

arXiv:2503.06340v2 Announce Type: replace-cross Abstract: Diffusion models have demonstrated remarkable generative capabilities in continuous data domains such as images and videos. Recently, discrete

Banger paper from Meta AI on research agents that decide what to investigate next. (bookmark it) If you run long-horizon research agents, ch…

Banger paper from Meta AI on research agents that decide what to investigate next. (bookmark it) If you run long-horizon research agents, choosing the next investigation is hard to learn, because thos

agentsdair-ai--x