Search: “persistence”

Characterizing Overconfident Failure in LLM-Based Code Generation

arXiv:2610.11300v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for automated code generation, but generated programs can appear syntactically plausible while stil

local-aiarxiv-cs-ai

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Coefficient Calibration as Selection Pressure in Symbolic Regression

DGX agent

arXiv:2610.10931v1 Announce Type: new Abstract: In memetic symbolic regression, candidate structures are compared after coefficient calibration, so the calibration protocol itself contributes to evolu

applicationsarxiv-cs-lg

9 Oct 2026

Defensive Sufficiency in a Stackelberg Model of AI Security

arXiv:2610.09892v2 Announce Type: replace-cross Abstract: Feedback from automated testing, human red teaming, and incident response can strengthen an AI system's defenses when discovered failures lead

Disentangling Linguistic and Paralinguistic Information with Routed Sparse Autoencoders

arXiv:2610.10865v1 Announce Type: new Abstract: Self-supervised speech encoders contain linguistic and paralinguistic information in a shared, entangled representation space. We combine a TopK sparse

researcharxiv-cs-cl

Evidence-Traceable Dynamic Interviewer Architecture for Expertise-Adaptive Qualitative Interviews Using Local LLMs

arXiv:2610.11651v1 Announce Type: new Abstract: Automated interviewers and conversational agents are increasingly used in research, recruitment, customer service, and education. However, many existing

local-aiarxiv-cs-ai

Explanation Multiplicity in SHAP: Characterization and Assessment

arXiv:2601.12654v3 Announce Type: replace-cross Abstract: SHAP explanations are widely used in high-stakes settings to justify decisions, yet they can differ substantially across repeated runs, even w

FlowState: Execution State as Memory for Long-Horizon LLM Agents

arXiv:2609.34565v2 Announce Type: replace Abstract: Long-horizon tasks require LLM agents to continually draw on information from earlier interactions. However, retaining the full history increases co

From Geometry to Generalization: Why Row Normalization Can Beat Adam and Muon

arXiv:2610.11309v1 Announce Type: cross Abstract: Different optimizers can fit the same training data while selecting classifiers with substantially different geometries, but whether this difference p

iAm.md: Robot Skill Self-Assessment through Agentic Introspection for Unknown Open-Vocabulary Domains

arXiv:2610.10962v1 Announce Type: cross Abstract: Agentic AI based on Large Language Model generalization capabilities offers a wide range of potential applications, including planning for embodied ta

agentsarxiv-cs-ai

Tutorials

ImagiNav: Scalable Embodied Navigation via Generative Visual Prediction and Inverse Dynamics

arXiv:2603.13833v2 Announce Type: replace Abstract: Enabling robots to navigate open-world environments via natural language is critical for general-purpose autonomy. Yet, Vision-Language Navigation h

tutorialsarxiv-cs-ro

Incremental Open-Ended Deep Research with Structured Harness

arXiv:2610.11566v1 Announce Type: new Abstract: Existing Open-Ended Deep Research (OEDR) systems primarily generate reports from scratch, making them inefficient for scenarios where research reports n

researcharxiv-cs-cl

Intervention anchors and scientific verification in synthetic vascular predictive representations

arXiv:2610.11704v1 Announce Type: new Abstract: Complete orthogonal predictive coordinates do not by themselves bind a latent direction to a named intervention. We present a mathematical and synthetic

agentsarxiv-cs-ai

Is Memorization Context-Sensitive? Prefix-Based Extraction Beyond Isolated Prefixes

arXiv:2610.12085v1 Announce Type: new Abstract: Large language models (LLMs) can expose memorized training sequences under prefix-based extraction: given a prefix from a training example, the model ma

Learning the Loop, Not Just the Page: Execution-Grounded Loop Learning for Web Generation

arXiv:2610.11543v1 Announce Type: new Abstract: Functional Web generation is increasingly optimized with executable rewards, yet existing methods largely focus on the quality of the final page and lea

safetyarxiv-cs-cl

Learning to Retrieve: Internalizing Memory Retrieval for Video World Models

arXiv:2610.11444v1 Announce Type: new Abstract: Video world models aim to generate explorable, 3D-consistent scene videos conditioned on camera trajectories. Existing approaches often rely on external

researcharxiv-cs-cv

Look Back, Think Ahead: Visual Memory on Demand for Efficient Multimodal Reasoning

arXiv:2610.12060v1 Announce Type: new Abstract: Processing long visual token sequences from high-resolution images makes multi-step reasoning computationally expensive for multimodal Large Language Mo

researcharxiv-cs-cv

Memento 3: Model-Based Recursive Self-Improvement through Reflective Rulebooks

arXiv:2610.11794v1 Announce Type: new Abstract: Learning to act in unfamiliar environments requires agents to infer how the world works and revise that understanding as new evidence arrives. Yet limit

agentsarxiv-cs-ai

Opera: A Verbal Critic Framework for Long-horizon Coding Agents

arXiv:2609.33987v2 Announce Type: replace Abstract: Long-horizon coding agents need timely corrections, yet feedback can be ineffective or even harmful when it misjudges ongoing work or fails to addre

safetyarxiv-cs-cl

PRAXIS: Learning Dynamics of Self-Improving Models with Symbolic Archives

arXiv:2610.11803v1 Announce Type: new Abstract: Self-improving learning systems adapt data selection, optimization, and auxiliary symbolic components, inducing nonstationary objectives outside standar

PulseBound: Future-Beat State Forecasting Under an Explicit Information Boundary

arXiv:2610.12010v1 Announce Type: new Abstract: Predictive representation learning from photoplethysmography (PPG) can violate causal information access even with causal attention, as normalization, n

REACT: Rolling Denoising and Dual Decoupling for Reactive Robot Control with VLA Models

arXiv:2610.12007v1 Announce Type: cross Abstract: Flow-based vision-language-action (VLA) models generate action chunks for temporally coherent robot motion, but chunked control creates a fundamental

Reading the Room: Foundations, Design, and Challenges of Normative Competence in LLMs

arXiv:2610.10906v1 Announce Type: new Abstract: Human communities are governed by normative systems: shared standards that produce extit{norms} dictating acceptable behavior, enforced through communit

RESETTLE: Robotic Recovery through Disagreement-Triggered Retrieval and Efficient Corrective Control

arXiv:2610.12185v1 Announce Type: new Abstract: Reliable robotic manipulation requires timely intervention to correct emerging deviations and restore progress after execution errors. However, recovery

safetyarxiv-cs-ro

ReTeach: Building a Self-Teacher through Multi-Round Reflection and Retry

arXiv:2610.11529v1 Announce Type: new Abstract: Self-distillation can improve reasoning without a separately trained, more capable teacher, but its effectiveness depends on how the self-teacher gains

SAVU-BENCH: A Real-World Benchmark for Spatial Audio-Visual Understanding

arXiv:2610.10624v1 Announce Type: cross Abstract: Spatial audio-visual understanding requires models to recognize not only what is present, but also where events occur and how they relate across modal

Scaling to Tens of Thousands of Test-Time Iterations with Loop-Native Attention Residuals

arXiv:2610.11570v1 Announce Type: new Abstract: In this paper, we argue that looped Transformers need their own residual connections to prevent performance degradation as the number of iterations grow

Self-Organization from Constrained Geometric Radiation

arXiv:2610.10621v1 Announce Type: new Abstract: How does dynamic order emerge spontaneously in closed systems without external driving? Existing paradigms all require external energy flows, temperatur

Slot3R: Set-Associative Spatial Memory for Streaming 3D Reconstruction

arXiv:2610.12282v1 Announce Type: new Abstract: Streaming 3D reconstruction must preserve evidence from each frame while processing an expanding scene online. Spatial memory is a natural fit because i

researcharxiv-cs-cv

Stop Probing, Start Coding: Why Linear Probes and Sparse Autoencoders Fail at Compositional Generalisation

arXiv:2603.28744v2 Announce Type: replace Abstract: The linear representation hypothesis states that neural network activations encode high-level concepts as linear mixtures. However, under superposit

Tutorials

Thinking Inertia: LLMs Keep Thinking When Told Not To

arXiv:2610.11765v1 Announce Type: new Abstract: Large Language Models (LLMs) increasingly ship with explicit 'thinking modes', yet their counterpart, 'no-thinking', has received far less attention. We

tutorialsarxiv-cs-cl

VAMR: Multi-Question Agentic Reasoning for Efficient Long-Form Video Understanding

arXiv:2610.11171v1 Announce Type: cross Abstract: Long-form video understanding often involves multiple questions about different aspects of the same recording. Yet existing video agents typically pro

When Routing Reveals Membership: Privacy Leakage from MoE Router Telemetry

arXiv:2610.10616v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) language models produce routing information during inference that may be logged or exposed for monitoring, debugging, load anal

safetyarxiv-cs-lg

When Scene Text Hijacks the Scene: Uncovering, Exploiting, and Mitigating Rendered-Text Semantic Leakage in Image Generation Models

arXiv:2610.11286v1 Announce Type: new Abstract: The reliability and accountability of image generative models (IGMs) are essential for building responsible and trustworthy AI systems. Recent IGMs, suc

local-aiarxiv-cs-cv

WOVEN: Weaving Visual World Modeling into Multimodal LLMs

arXiv:2610.12417v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) struggle with spatial, embodied, physical, and temporal reasoning. We hypothesize that these failures reflect

A Deafening Silence: Catastrophic Forgetting Lives in the Output Embeddings of Tokens the Data Never Speaks

arXiv:2610.09835v1 Announce Type: new Abstract: Continual pre-training and fine-tuning in Large Language Models (LLMs) inevitably induce catastrophic forgetting, typically mitigated by replay using of

A Geometry-Based Capacity Theory for Finite-Feature Associative Memory

arXiv:2610.09056v1 Announce Type: new Abstract: We develop a geometry-based capacity theory for exact-key retrieval in compressed finite-feature Hebbian associative memory. For random or approximately

CATune: Structural Constraint-Aware Bayesian Optimization for DBMS Configuration Tuning

arXiv:2610.09276v1 Announce Type: cross Abstract: Modern DBMSs expose hundreds of configuration knobs, resulting in a high-dimensional and heterogeneous search space that makes automated tuning costly

COPC: Coupled Off-Policy Correction for Asynchronous LLM Reinforcement Learning

arXiv:2610.09597v1 Announce Type: new Abstract: Asynchronous RL accelerates large language model post-training by decoupling rollout generation from optimization, but trains on stale trajectories. Exi

{Delta}WAM: Distilling Action Tangent Fields into World Action Models

arXiv:2610.09734v1 Announce Type: new Abstract: World Action Models (WAM) improve robot policies by augmenting sparse action supervision with dense future prediction. However, much of the predictable

local-aiarxiv-cs-ro

Despite Instructions: Frontier Agents Improvise Covert Channels at Test Time

arXiv:2609.32701v2 Announce Type: replace-cross Abstract: In security-sensitive applications, language-model agents are often required to coordinate without disclosing confidential information. Yet re

Diffusion-Generated Image Watermarking: A Two-Axis Taxonomy and Three Protocol-Bounded Case Studies

model-releasesarxiv-cs-cv

arXiv:2610.09755v1 Announce Type: new Abstract: Watermarking diffusion-generated images requires balancing provenance signals with image quality, robustness, and computational cost. This work organize

ExperienceIndex: Artifact-Grounded Memory

arXiv:2610.10091v1 Announce Type: new Abstract: Knowledge-intensive tasks require answering many questions by reasoning about a shared corpus of artifacts (e.g., court cases, or scientific literature)

agentsarxiv-cs-cl

HAN-Mamba: Hierarchical Selective State Space Networks for Multi-Scale Financial Volatility Forecasting

arXiv:2610.10323v1 Announce Type: new Abstract: Short-horizon realized volatility forecasting requires the integration of market information that evolves at incompatible temporal resolutions, from sec

Homogenization in Multi-Agent Systems

arXiv:2610.09824v1 Announce Type: new Abstract: Multi-agent systems (MAS) leverage interactions between agents to perform complex tasks. Despite their success, we show that these interactions can also

agentsarxiv-cs-lg

Input-Blind Controls Produce Substantial Oracle Headroom for Layer Programs in Multiple-Choice Evaluation

arXiv:2610.10368v1 Announce Type: cross Abstract: Adaptive computation aims to improve language-model inference by tailoring execution to each input. For layer programs, oracle evaluations use known a

Large-scale Repository Engineering via Agent-Native Reusable Code Primitives

arXiv:2610.09079v1 Announce Type: cross Abstract: Large language models equipped with development environments have moved code generation toward repository-scale construction, yet building complete re

Learning joint probabilistic weather forecasts from station observations alone

arXiv:2610.09898v1 Announce Type: cross Abstract: Assessing compound weather risks requires forecasts representing dependence between variables. CLARA (Calibrated Advection-Routing Attention) learns j

Many Ways to Succeed: Diversity-Driven RL Fine-Tuning for VLA Generalization

arXiv:2610.09943v1 Announce Type: cross Abstract: Reinforcement learning (RL) fine-tuning improves vision-language-action (VLA) policies through closed-loop experience, yet generalization beyond the f

safetyarxiv-cs-lg