Search: “persistence”

Causal Analysis for Time Series Foundation Models

arXiv:2608.24303v1 Announce Type: new Abstract: Transitioning from bespoke time series models towards time series foundation models changes the relationship of model and application from one-to-one to

safetyarxiv-cs-lg

Human

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Do Recipes Have Personas? Characterizing and Generating Creator Style in Attributed Procedural Graphs

DGX agent

arXiv:2608.24369v1 Announce Type: new Abstract: While large language models (LLMs) possess vast zero-shot procedural knowledge, their tendency to produce homogenized logic often obscures the unique, i

local-aiarxiv-cs-ai

26 Aug 2026

Dynamical System-Based Imitation Learning and Neuroadaptive Control for Trajectory Recovery in Autonomous Ships

arXiv:2608.23924v1 Announce Type: cross Abstract: Repetitive maritime operations can be effectively learned using the Imitation Learning (IL) paradigm, which transfers human expertise directly to Unma

safetyarxiv-cs-ro

EgoErrorVQA: Assess Egocentric Comprehension Capabilities through Procedural Errors for Ego-Agentic AI

arXiv:2608.24134v1 Announce Type: new Abstract: The majority of our everyday activities are procedural and consist of sequences of interdependent steps. However, existing benchmarks for Visual Agents

agentsarxiv-cs-cv

Eluna: An Agentic LLM System for Automating Warehouse Operations with Reasoning and Task Execution

arXiv:2607.08960v2 Announce Type: replace-cross Abstract: Warehouse operations are governed by Standard Operating Procedures (SOPs) that encode complex, multi-system decision logic, which must be exec

Hierarchical Prototype-Memory Adaptation of SAM for Surgical Instrument Segmentation

arXiv:2608.24541v1 Announce Type: new Abstract: Surgical instrument segmentation (SIS) is fundamental for computer-assisted surgery, where reliable instrument masks enable precise scene understanding

local-aiarxiv-cs-cv

Matched Excess-Outranker Regularization for Candidate-Set Interference in Continual Knowledge Graph Embedding

arXiv:2608.24273v1 Announce Type: new Abstract: Continual knowledge graph embedding updates entity and relation representations as a graph grows. Existing methods primarily address catastrophic forget

Memory Is Not Always Needed: Characterizing Conditional Memory in Scientific Reasoning

arXiv:2608.23982v1 Announce Type: new Abstract: Scientific reasoning requires language models to retrieve specialized knowledge and incorporate it reliably into multi-step computation. Conditional mem

NeurRAFT: Robot Motion Planning via Anchor-Level Flow Matching with Clearance-Aware Preference Tuning

arXiv:2608.24026v1 Announce Type: new Abstract: Recent end-to-end neural motion planners generate trajectories from raw sensor observations, avoiding the privileged geometric models required by classi

local-aiarxiv-cs-ro

Hardware

Nvidia forecasts Q3 revenue of 108B, above a 104B estimate, and expects FY 2028 revenue to grow by about 70%; NVDA jumps 4%+ after hours (Deborah Mary Sophia/Reuters)

Deborah Mary Sophia / Reuters: Nvidia forecasts Q3 revenue of 108B, above a 104B estimate, and expects FY 2028 revenue to grow by about 70%; NVDA jumps 4%+ after hours — Nvidia's (NVDA.O) quarterly re

hardwaretechmeme

Orchestration is the new challenge for CX in the age of AI agents

Presented by Tata Communications Enterprises are deploying AI agents, voice AI, and automation across messaging, voice, and digital channels faster than the architecture meant to support it. Most of t

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Predictability of El Nino from Delayed Observations

arXiv:2608.24428v1 Announce Type: cross Abstract: Using monthly Nino-3.4 anomalies through July 2026, we investigate how much predictive information is contained in delayed observations of the index.

RENDER: Controlling Reader-Facing Evidence in LLM Memory Evaluation

arXiv:2608.23568v1 Announce Type: new Abstract: Memory and RAG evaluations often treat the answering model's input as an implementation detail, even though systems may render the same history as a mem

ReproAgent: Contract-Guided Paper-to-Code Reproduction

arXiv:2608.24291v1 Announce Type: new Abstract: Paper-to-code reproduction asks scientific AI agents to turn research papers into executable repositories that preserve the paper's method, protocol and

Scientific Image Synthesis: Benchmarking, Methodologies, and Downstream Utility

arXiv:2601.17027v2 Announce Type: replace-cross Abstract: While synthetic data has proven effective for improving scientific reasoning in the text domain, multimodal reasoning remains constrained by t

SPO++: Stream-Aligned Policy Optimization for Asynchronous Agentic RL

arXiv:2608.24870v1 Announce Type: new Abstract: Group-relative reinforcement learning waits for sibling rollouts of the same prompt, which is costly for long and variable tool-use trajectories. Single

STAIN-FL: Stealthy Targeted Attack Injection with Contextual Triggers in Federated Learning

arXiv:2608.23952v1 Announce Type: cross Abstract: Federated video anomaly detection trains model collaboratively without sharing raw surveillance footage, but limited server-side visibility lets compr

The Empire, Long Divided, Must Unite: Architectural Convergence in Three LLM Agent Harnesses

arXiv:2608.23953v1 Announce Type: cross Abstract: An agent harness is what turns a language model into an autonomous agent: the surrounding code that builds the model's context, mediates its tools, ru

A Commutator Framework for Selective Spectral Alignment in Deep Neural Networks

arXiv:2608.22910v1 Announce Type: cross Abstract: We develop a finite-width geometric framework describing how learned feature geometries are organized, transported, and selectively aligned in deep ne

safetyarxiv-cs-lg

A Survey on Human-AI Collaboration with Large Foundation Models

arXiv:2403.04931v4 Announce Type: replace Abstract: As the capabilities of artificial intelligence (AI) continue to expand rapidly, Human-AI (HAI) Collaboration, combining human intellect and AI syste

Agentic Scaffolding Amplifies Sycophantic Behavior in Large Language Models

arXiv:2608.21377v1 Announce Type: cross Abstract: Sycophancy in large language models, the tendency to prioritize user agreement over truthful responses, has been documented extensively but studied pr

agentsarxiv-cs-ai

Arbitrage-Aware Multi-Step Forecasting of Implied Volatility Surfaces: Modelling Surface Trajectories Using Latent Diffusion

model-releasesarxiv-cs-lg

arXiv:2608.22478v1 Announce Type: cross Abstract: Implied volatility surfaces summarise the option market and are central to many financial applications. Forecasting their future evolution requires mo

Beyond Fixed Directions: Adaptive Representation Analysis of Reasoning and Memorization in LLMs

arXiv:2608.21919v1 Announce Type: new Abstract: Recent work has proposed that reasoning and memorization in language models can be characterized by a single representation direction, including methods

CausalCache: Conditional High-Fidelity Restoration for Long-Horizon GUI Agents

arXiv:2608.22577v1 Announce Type: new Abstract: Long-horizon GUI agents can retain a complete interaction trace cheaply as textual action records, but expose only a few past events to the policy in hi

ChainPrune: Evaluating and Reducing Redundancy in Long Chain-of-Thought Reasoning

arXiv:2608.21860v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) reasoning has significantly enhanced the multi-step problem-solving capabilities of large language models (LLMs) by introducing

Context as an Environment: Programmatic Context Management for Long-Horizon Agents

arXiv:2608.21690v1 Announce Type: new Abstract: LLM agents increasingly take on long-running tasks whose history grows far beyond a single model context window. Existing approaches compress earlier in

DesignAgent3D: Interactive 3D Scene Editing via Designer-like Multimodal Reasoning

arXiv:2608.21438v1 Announce Type: new Abstract: Text guided 3D scene editing provides an intuitive interface for modifying reconstructed environments, but remains difficult because natural language de

safetyarxiv-cs-cv

EDGE: Experience-Distillation for Guided Exploration in Agentic Reinforcement Learning

arXiv:2608.21946v1 Announce Type: cross Abstract: Reinforcement learning with outcome-based objectives such as GRPO enables LLM-based agents to solve complex, long-horizon tasks, yet the reusable expl

FinAcumen: Financial Multimodal Reasoning via Self-Evolving Experience Memory Harness

arXiv:2606.17642v3 Announce Type: replace Abstract: Financial multimodal reasoning requires agents to coordinate numerical computation, retrieval, visual interpretation, and temporal grounding across

agentsarxiv-cs-ai

Forgetting to Forget: Attention Sink as A Gateway for Backdooring LLM Unlearning

arXiv:2510.17021v2 Announce Type: replace-cross Abstract: Large language model (LLM) unlearning is a key approach for removing undesired data, knowledge, or behaviors from pretrained models while reta

researcharxiv-cs-cl

Tutorials

FreKoo++: Learning Continuous Spectral Dynamics for Temporal Domain Generalization

arXiv:2608.22224v1 Announce Type: cross Abstract: Temporal Domain Generalization (TDG) aims to learn from historical domains and generalize to unseen future distributions under concept drift. Neverthe

tutorialsarxiv-cs-ai

HERO: Human-profile Enhanced Retrieval Optimization Framework for Long-term Agent Memory

arXiv:2608.22310v1 Announce Type: new Abstract: Long-term memory is crucial for personalized responses and long-horizon agent interactions. Existing methods often rely on LLMs to compress or rewrite d

Impressive work from Alibaba. (bookmark it) If you build long-running agents and keep rewriting your memory schema, take a look at this appr…

Impressive work from Alibaba. (bookmark it) If you build long-running agents and keep rewriting your memory schema, take a look at this approach. It basically treats agent context management as a prog

agentsdair-ai--x

Last But Not Least: Boundary Attention CalibratiON for Multimodal KV Cache Compression

arXiv:2606.14782v3 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) achieve strong vision-language reasoning but incur large KV caches and high decoding latency with lon

researcharxiv-cs-cl

Lightweight Multi-scale Hierarchical Anomaly Detection and Localization for Geospatial Big Data Applications at the Edge

arXiv:2608.22648v1 Announce Type: cross Abstract: As an increasing number of critical applications, including environmental, emergency, meteorological, and agricultural, rely on real-time anomaly dete

MEMORY Wins All: Indirect Bias Injection Attacks via Social Media Feeds

arXiv:2608.22061v1 Announce Type: new Abstract: Personal AI agents routinely consume external content while performing tasks such as web browsing, email processing, and SNS feed summarization, and the

Model of Models: When Does Emitting a Specialist Beat Attending, Adapting, or Tuning?

arXiv:2608.21386v1 Announce Type: cross Abstract: Given a task described by a few examples, how should a model be specialized to it? Four mechanisms are available -- zero-shot, in-context attention, t

Mycelial Search: A Graph-Structured Metaheuristic for Continuous Optimisation

arXiv:2608.23323v1 Announce Type: cross Abstract: Continuous optimisation methods need to balance sharing information and maintaining alternative search directions. In this paper, we introduce Mycelia

NeuroPrefetcher: Storage-Aware Sparse LLM Inference via Delta Prefetching

model-releasesarxiv-cs-lg

arXiv:2608.22643v1 Announce Type: cross Abstract: Deploying large language models on edge devices is increasingly limited by a widening gap between model size and available memory. Existing approaches

Hardware

Prime Agent: A Self-Improving RLM Harness

arXiv:2608.23552v1 Announce Type: new Abstract: Language models are sequential processors, but long-horizon agency requires external information and computation beyond model weights and active context

hardwarearxiv-cs-ai

ProxyFormer: A Dual-Stream Proxy Architecture for Ultra-Long Context and High-Resolution Generation

arXiv:2608.23463v1 Announce Type: new Abstract: The quadratic growth of attention computation and key-value (KV) cache with respect to sequence length is a central bottleneck for ultra-long-context la

local-aiarxiv-cs-lg

RAG Collapse: LLM Responses Collapse When Retrieved Documents Are Self-Authored

arXiv:2608.22118v1 Announce Type: new Abstract: LLM responses are based on the internet (via training or RAG), and AI is now used to generate a significant amount of content online (Paredes et al., 20

safetyarxiv-cs-cl

SANE: State Anomaly Neutralization for Stable Extreme-Context Delta-Rule Models

arXiv:2608.22354v1 Announce Type: cross Abstract: Delta-Rule recurrent models maintain a fixed-size state, enabling O(1) inference memory but potentially becoming unstable under extreme-context extrap

Spectral partitioning for k-block averaging kernels of finite Markov chains

arXiv:2608.21466v1 Announce Type: cross Abstract: We develop spectral algorithms for selecting state-space partitions that define averaging kernels for finite, ergodic and reversible Markov chains. Fo

SSDi8: Accurate and Efficient 8-bit Quantization for State Space Duality

arXiv:2608.21952v1 Announce Type: new Abstract: Recent advances in sequence modeling have highlighted Mamba as a state space architecture offering efficient long-range dependency modeling and providin

ST^2U: Stateful Test-Time Unlearning via Restricted Knowledge Boundary Control

model-releasesarxiv-cs-cl

arXiv:2608.23034v1 Announce Type: cross Abstract: Controlling restricted knowledge in large language models is essential for model alignment and safe deployment. Test-time unlearning avoids costly ret

Training Needs Trustworthy Worlds: Verified Synthetic Web Environments for Agent Learning

arXiv:2608.21898v1 Announce Type: new Abstract: Web agents promise to automate complex digital workflows, but their training remains limited by synthetic environments that look plausible while hiding

Unlearning Is Not Just Erasing: Temporal Decoupling via Generation Inequality

arXiv:2608.23020v1 Announce Type: cross Abstract: Large language models (LLMs) require effective unlearning to address privacy regulations and safety concerns. However, achieving precise forgetting wi

local-aiarxiv-cs-ai