Search: “persistence”

iS-KV: Online Low-Rank KV Cache Compression via Block-Incremental SVD

arXiv:2610.02815v1 Announce Type: new Abstract: Long chain-of-thought reasoning substantially increases KV-cache memory during autoregressive decoding, as every generated token introduces new key and

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Large language models exhibit unreliable updating of clinical judgment as patient evidence evolves

DGX agent

arXiv:2610.02684v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly explored for clinical reasoning, but whether they appropriately revise judgments as patient evidence evolv

researcharxiv-cs-ai

5 Oct 2026

Learning What to Investigate Next: Meta-Reasoning for Long-Horizon Research Agents

arXiv:2610.02525v1 Announce Type: new Abstract: Long-horizon research agents must decide both how to investigate and what to investigate next as evidence accumulates. This is hard to learn because suc

LPS-Bench: Benchmarking Safety Awareness of Computer-Use Agents in Long-Horizon Planning under Benign and Adversarial Scenarios

arXiv:2602.03255v2 Announce Type: replace Abstract: Computer-use agents (CUAs) execute multi-stage tasks through tools, where an early unsafe decision can propagate to consequential actions. Evaluatin

LS-AR: Future-Predictive Latent Steering in Autoregressive LLMs

model-releasesarxiv-cs-lg

arXiv:2610.03093v1 Announce Type: new Abstract: Standard autoregressive (AR) models process high-level task instructions, state history, and transient tokens within a single shared sequence of tokens.

LUMOS: Tracing Parametric Knowledge from Training Data to Behavioral Outputs in LLMs

arXiv:2610.02902v1 Announce Type: new Abstract: Current analyses of LLMs' parametric knowledge are largely output-centric, drawing conclusions about what a model knows without verifying what it was ac

MetaRubric: Learning to Reward for Rubric-Based Reinforcement Learning

arXiv:2610.02824v1 Announce Type: new Abstract: Rubric-based reinforcement learning extends reward-driven optimization to open-ended tasks by assigning partial credit to individual response requiremen

Neural Data Needs Semantic Tokenization: Behavioral Events as Boundaries of Session-Transferable Tokens

arXiv:2610.03001v1 Announce Type: new Abstract: Extracellular electrophysiology records a different set of neurons in every session. Neural foundation models embed each neuron and each session into th

OuroReward: Sequential Reward Scheduling for Reinforcement Learning in Text-to-3D Generation

arXiv:2610.03423v1 Announce Type: new Abstract: Reinforcement learning (RL) for Text-to-3D (T23D) generation requires optimization across multiple quality dimensions such as semantic alignment and tex

PAPER2LLM++: Continual Self-Evolution of LLMs from Research Papers

arXiv:2610.02793v1 Announce Type: new Abstract: Research on LLMs continually uncovers model limitations, their causes, and potential solutions. Yet these human discoveries remain largely disconnected

tutorialsarxiv-cs-ai

RAOA: Alternating-Operator Neural Computation with Programmable Radio Propagation

arXiv:2610.02683v1 Announce Type: new Abstract: Can programmable radio propagation serve as computational depth rather than only as a communication channel or one-shot analog transform? We introduce t

RoboBridge: A Self-Evolving Embodied Agent Framework for Sim-to-Real Transfer

arXiv:2610.02717v1 Announce Type: new Abstract: A key challenge in bringing embodied intelligence into the real world is transferring capabilities from simulation to reality and enabling agents to con

safetyarxiv-cs-ro

SEDIMA: Cross-Run Hierarchical Insight Memory for Evolutionary Search Agents

arXiv:2610.02361v1 Announce Type: cross Abstract: Large language model (LLM)-driven evolutionary search is a powerful paradigm for automated program and algorithm discovery, yet existing systems are l

researcharxiv-cs-cl

The Surprising Effectiveness of Shared Memory in Looped Transformers

arXiv:2610.02383v1 Announce Type: cross Abstract: Looped Transformers apply the same layers several times per token, adding compute to improve quality without more parameters. Each recursion, however,

To Explore The Strange New World Beyond Data Distribution: System Behavior, Causality Tax, and Non-causal Base Model

arXiv:2610.02839v1 Announce Type: cross Abstract: We show that the causality of language models (LMs) may not be necessary nor optimal. This is the case when system behavior (denoted as S) is incorpor

researcharxiv-cs-cl

When History Fails to Become Experience: Action Calibration in Language Agents

arXiv:2610.02769v1 Announce Type: cross Abstract: Language agents should draw on prior attempts and environmental feedback to improve subsequent decisions within the same task. However, providing addi

tutorialsarxiv-cs-ai

World Editing: Intervening on Executable Worlds at Increasing Depth

arXiv:2610.02331v1 Announce Type: new Abstract: Interactive world models are increasingly capable of generating environments and acting within them, yet deliberately editing an existing executable wor

I agree that chatgpt/codex has the current best agent interface for deep work. - It unifies all my work (coding/knowledge work) in one inter…

model-releasesjerry-liu--x

I agree that chatgpt/codex has the current best agent interface for deep work. - It unifies all my work (coding/knowledge work) in one interface. Toggling between chatgpt/codex doesn't have explicitly

4 Oct 2026

Syntheses

Wiki Lint Report — 2026-10-04

linthealth-checkautomated

Automated lint: 19 errors, 64915 warnings, 3 info

4 Oct 2026

Syntheses

Synthesis: Arxiv-Cs-Ro

synthesisarxiv-cs-roauto-generated

Auto-generated synthesis of 5773 entries about arxiv-cs-ro

4 Oct 2026

A Comprehensive Review of One-Pixel Attack: Research Status, Taxonomy, Applications, Regulation Policy and Future Directions

arXiv:2610.00125v1 Announce Type: cross Abstract: One-Pixel Attacks (OPAs) represent one of the most extreme demonstrations of adversarial fragility in deep learning, where modifying a single pixel ca

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

Action-On-Item Preference Flow: A Shared Event Schema for Predictive and Generative Personalization

arXiv:2610.01375v1 Announce Type: new Abstract: A user's movie, news, and dialogue histories differ in their native actions and outputs, yet each interaction supplies evidence that can update user mem

Actions with Receipts: Jointly Binding Claims, Evidence, and Execution for Replayable Tool-Agent Auditing

arXiv:2610.00327v1 Announce Type: cross Abstract: Tool-using agents can expose citations and execution logs while leaving a critical association unaudited: whether the claim shown to a user is the cla

agentsarxiv-cs-ai

AI Emulation of Stochastic Sudden Stratospheric Warming with Interpretable Latent Structure

arXiv:2610.02069v1 Announce Type: cross Abstract: Rare weather regime transitions pose a challenge for data-driven modeling due to class imbalance. In this study, we develop a probabilistic deep learn

An ontology for cross-sectoral crisis management: core and public health modules

arXiv:2610.01326v1 Announce Type: new Abstract: This paper presents the European Crisis Management Ontology (ECMO), a modular OWL-based ontology intended as a cross-sectoral reference for disaster ris

Architectural Sampling: Test-Time Scaling via Computational Diversity in Frozen Vision-Language Models

arXiv:2610.01687v1 Announce Type: cross Abstract: Test-time scaling often seeks better answers by sampling multiple responses from a frozen model, yet conventional temperature sampling generates every

Are We Recovering Mechanisms? Objective-Level Recovery Gaps in Mechanistic Interpretability

arXiv:2610.02098v1 Announce Type: new Abstract: Mechanistic interpretability aims to recover the internal computations responsible for model behavior. Progress in automated circuit discovery is often

Asynchronous LLM Post-Training: Group-Mass Capping and Convergence Analysis

arXiv:2610.01896v1 Announce Type: cross Abstract: Asynchronous reinforcement learning (RL) improves the efficiency of large language model post-training but introduces stale rollouts generated by earl

Atoms to Processes: The Role of Artificial Intelligence and Machine Learning in Chemical Engineering

arXiv:2610.02014v1 Announce Type: new Abstract: The rapid maturation of artificial intelligence (AI) and machine learning (ML) has catalyzed a profound shift in how chemical engineering problems are f

agentsarxiv-cs-ai

Before It Fades: Reinforcing Temporal Representations at Inference Time in VideoLLMs

arXiv:2610.01595v1 Announce Type: cross Abstract: Video Large Language Models (VideoLLMs) receive frames in sequential order and interpret how visual content evolves along the temporal axis, yet tempo

BG4Sea: Biogeochemical Seasonal Forecastability via Progressive Information Scaling

arXiv:2607.16731v2 Announce Type: replace Abstract: Marine biogeochemical forecasting is increasingly important for managing marine ecosystems and the carbon cycle, yet global, seasonal forecast produ

Causal Memory Policy: Making Memory Utility Identifiable by Intervening on Retrieval

arXiv:2610.02070v1 Announce Type: new Abstract: Memory-augmented large language models must decide which memories to retain, and recent systems do so by estimating each memory's effect on task perform

CoEvolve: Construct-to-Edit Visual Grounding with Bidirectional State Refinement

arXiv:2610.01710v1 Announce Type: new Abstract: Visual grounding localizes an object described by language with a bounding box. Most multimodal grounding models compress target identification, spatial

Contrastive Attention Mitigates Spectral Bias in Spiking Transformers

arXiv:2610.01403v1 Announce Type: new Abstract: Spiking Transformers merge the energy-efficiency of spiking neural networks (SNNs) with the representational power of self-attention, creating a promisi

Designing for Interpretation Uncertainty: Architecture and Principles for Topological Learning Analytics Dashboards

arXiv:2610.01749v1 Announce Type: cross Abstract: Topological Data Analysis (TDA) offers novel methods for understanding temporal dynamics in complex systems, yet its application in information system

DiVid: Diagnosing Dimension-Specific Diversity Collapse in Video Generation Models

model-releasesarxiv-cs-cv

arXiv:2610.01661v1 Announce Type: new Abstract: Despite remarkable progress, video generation models often produce highly similar outputs when repeatedly sampled from the same prompt, limiting their u

Domain generalization and synthetic data in object detection: the enabler, the probe, and the gap

arXiv:2610.00030v1 Announce Type: new Abstract: Object detection models often experience performance degradation when deployed under distribution shifts, caused by for example changes in weather type,

DramaAgent: Agentic Storytelling Video Generation

arXiv:2610.00097v1 Announce Type: new Abstract: Recent diffusion and autoregressive models have substantially improved text-to-video generation, yet producing coherent long-form story videos with cons

agentsarxiv-cs-cv

ECoMEM: Explicit Concept Memory for Memory-Dependent Robot Control

arXiv:2610.00801v1 Announce Type: new Abstract: A robot may lose sight of an object it must later retrieve, need to recall what a person demonstrated earlier, or track which steps of a task it has alr

safetyarxiv-cs-ro

Ego2Act: Evaluating Goal-Directed Manipulation in Egocentric Video Generation

model-releasesarxiv-cs-cv

arXiv:2610.01092v1 Announce Type: new Abstract: Video generation models are increasingly being explored as world simulators for embodied planning and learning. To do so effectively, these models must

Empty Commitments: When Agents Promise What Their Runtime Cannot Deliver

arXiv:2610.01045v1 Announce Type: new Abstract: A chatbot that says 'I will remind you tomorrow' will not run again until the user writes. We call such a promise an empty commitment: a promise of an a

agentsarxiv-cs-ai

Applications

Energy Time-Series Imputation with Differentially Private Diffusion Models via Clipping-Aware Objective Conditioning

arXiv:2610.00209v1 Announce Type: new Abstract: Reliable recovery of missing measurements is important for monitoring and analysis in energy time-series systems, where fine-grained measurements may co

applicationsarxiv-cs-lg

EvoGen-Harness: Learning Where and How to Evolve Image-Generation Harnesses

arXiv:2610.00383v1 Announce Type: new Abstract: Modern text-to-image (T2I) systems can be improved without modifying generator parameters by adapting the external system around frozen generators. Howe

tutorialsarxiv-cs-lg

Exploring More, Reasoning Better: Stepwise Risk-Sensitive GRPO for Diffusion Language Models

arXiv:2610.00661v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text by denoising a sequence or successive blocks, allowing several tokens to be revealed in parallel

tutorialsarxiv-cs-ai

Applications

Exponential quantum advantage in processing massive classical data

arXiv:2604.07639v2 Announce Type: replace-cross Abstract: Broadly applicable quantum advantage, particularly in classical data processing and machine learning, has been a fundamental open problem. In

applicationsarxiv-cs-ai

EyeTAG: Eye Trajectory-Aware Gaze Estimation

arXiv:2610.00922v1 Announce Type: new Abstract: Gaze estimation under natural head-eye motion underpins applications from driver monitoring to human-computer interaction. Single-frame methods predict

Fault-Tolerant Budget Conservation in Distributed Multi-Agent Delegation

arXiv:2610.00349v1 Announce Type: new Abstract: Resource limits are becoming an authorization boundary for AI agents that delegate work across concurrent and failure-prone workers. Parent-child alloca