Search: “persistence”

RoofLang: Enabling AI-Driven Architecting of LLM Inference Systems

model-releasesarxiv-cs-ai

arXiv:2609.12551v2 Announce Type: replace-cross Abstract: AI is beginning to make substantive contributions to LLM inference optimization. Existing AI optimizations are predominantly profiling-based.

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Safety

SG-CPG: Severity-Gated Central Pattern Generators for Adaptive Quadruped Locomotion under Continuous Actuator Degradation

DGX agent

arXiv:2609.25687v1 Announce Type: new Abstract: An animal with a weakened limb does not necessarily switch its gait, instead it unloads the affected limb, re-coordinates the remaining limbs, and scale

safetyarxiv-cs-ro

23 Sept 2026

Slow Decay and Silenced Expression: Iterated Subliminal Trait Transfer in Language-Model Lineages

arXiv:2609.25721v1 Announce Type: cross Abstract: Language models are increasingly trained on the outputs of other models, forming chains that we call lineages, in which a trait present in one generat

researcharxiv-cs-cl

Applications

StrataVLA: Hierarchical and Efficient 3D Geometric Grounding for Vision-Language-Action Models

arXiv:2609.26071v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models inherit strong semantic priors from large-scale vision-language pretraining, yet remain limited in robotic manipulat

applicationsarxiv-cs-ro

Toward Self-Repairing Ubiquitous Robots Using Goal-Oriented Agentic AI in Human-Robot Interactions

arXiv:2609.26155v1 Announce Type: new Abstract: Ubiquitous robotic systems often lack traditional visual interfaces, making natural language interaction important for maintenance and repair. This pape

agentsarxiv-cs-ro

TRACE: Trajectory Representation and Consistency Estimation for AI-Generated Video Detection

arXiv:2609.25775v1 Announce Type: new Abstract: Recent advances in generative video models have enabled the synthesis of visually realistic content, posing significant challenges to synthetic video de

researcharxiv-cs-cv

Trustworthy Agentic AI: Failure Modes, Mitigation Strategies, and a Lifecycle Framework for Autonomous LLM Systems

arXiv:2609.22712v1 Announce Type: new Abstract: Agentic AI systems built on large language models can plan over multiple steps, use external tools, retain information in memory, and coordinate with ot

safetyarxiv-cs-ai

Truth for Believable AI: Expressed Doubt, Provenance, and Belief Revision as an Engineerable Stance

arXiv:2609.26035v1 Announce Type: new Abstract: Conversational agents often express answers in a uniformly confident register. We test whether expressed uncertainty, provenance-aware assertion, and ex

Underwater Navigation in Unsteady Flows Using Measurement Histories from a Single Sensing Unit

arXiv:2609.26753v1 Announce Type: new Abstract: Spatial flow measurements support underwater navigation, but distributed sensing is constrained by robot size and sensor layout. We use a causal observe

researcharxiv-cs-ro

When are bosonic Gaussian states classical to learn?

arXiv:2609.26705v1 Announce Type: cross Abstract: A fundamental question in physics is: When does classical behavior emerge from quantum systems? Bosonic Gaussian states provide a natural setting to e

WidgetVA: A Widget-Centric Framework and Benchmark for Agentic Visual Analytics

model-releasesarxiv-cs-ai

arXiv:2609.24094v1 Announce Type: cross Abstract: Visual analytics (VA) enables sensemaking through interactive visualization, but effective analysis often requires experts to translate high-level int

Ananke: Contractive Torus Attractor Networks

arXiv:2609.24737v1 Announce Type: new Abstract: We introduce Ananke, a representation-learning framework that scaffolds latent representations onto a structured product-torus prior, and its flagship v

Anatomy of a Closed-Loop Collapse: A Causal Case Study of a Compressed VLA Policy

arXiv:2609.23048v1 Announce Type: cross Abstract: Compressed manipulation policies can pass offline evaluation while failing in closed-loop execution; this dissociation is established in prior work an

safetyarxiv-cs-lg

Barrier Certificate Synthesis for Non-Polynomial Robotic Dynamics via Polynomial Lifting

arXiv:2609.22885v1 Announce Type: new Abstract: Safe operation of robotic systems requires trajectories to remain within a prescribed safe set under admissible control inputs. Barrier certificates pro

safetyarxiv-cs-ro

Beyond Average Error through Oracle-Informed Stress Tests for Time-Series Forecasting

arXiv:2609.22820v1 Announce Type: new Abstract: Average squared error cannot reveal whether forecasting performance degrades because the future becomes less predictable or because forecasts move farth

CALM: A Calibrated LLM Choice Network Framework for Activity-Based Traveler Simulation

arXiv:2609.22252v1 Announce Type: new Abstract: We present CALM, a reproducible hybrid framework that integrates an optional large language model (LLM) activity planner with calibrated stochastic choi

Constrained Decoding Eliminates Structural Failures in Small LLMs but Reveals a Scale-Dependent Semantic Gap

arXiv:2609.23742v1 Announce Type: new Abstract: Small open-source large language models (LLMs) in the 0.6B-4B parameter range are increasingly deployed for structured output generation (JSON, function

Cost-Aware Reinforcement Learning with Action Masking and Projection for Battery Energy Storage Dispatch under Suppressed-Spread Market Shifts

arXiv:2609.23590v1 Announce Type: new Abstract: Battery energy storage system (BESS) dispatch must preserve operational feasibility while declining price spreads reduce the margin available to pay for

safetyarxiv-cs-lg

Local Ai

Dissecting Agentic Forensics: The Role of Triage, Prompting, and Evidence Arbitration in Open-World Fake Image Detection

arXiv:2609.24359v1 Announce Type: new Abstract: Image forensics is increasingly an open-world problem: manipulations range from fully synthetic images to localized edits, splicing and swapping, while

local-aiarxiv-cs-cv

Dissecting Hierarchical Reasoning Models: A Mechanistic Study

arXiv:2609.22197v1 Announce Type: new Abstract: We study Hierarchical Reasoning Model (HRM), a representative hierarchical Transformer-based latent reasoning model with many variants, on Sudoku, Maze,

Do LiDAR Language Models Really Understand Spatio-temporal Relationships?

arXiv:2609.24452v1 Announce Type: new Abstract: Recent 4D LiDAR language models aim to reason about objects and their evolving spatial relationships. Yet, in our evaluation, always selecting the same

EvoRank: LLM-Guided Evolution of Multi-Objective Learning-to-Rank Pipelines

arXiv:2609.22196v1 Announce Type: cross Abstract: We present EvoRank, an open autonomous ranking engineer: an LLM-guided evolutionary loop that discovers complete Learning-to-Rank pipelines (features,

agentsarxiv-cs-cl

Fathom-Vaidya: Advancing Medical Reasoning with Rubric-Based Rewards

arXiv:2609.24480v1 Announce Type: cross Abstract: Deploying Large Language Models (LLMs) in healthcare requires robust performance across two complementary dimensions - diagnostic reasoning: the conve

Finite Topological Space Filtrations: A Topological Framework for Data Analysis

arXiv:2512.23348v3 Announce Type: replace-cross Abstract: We introduce a data-analysis framework based on filtrations of finite topological spaces. Starting from a finite metric data set, we construct

Functional Emotion Without Character: Large Language Models, Aristotelian Disposition, and the Limits of Behavioral Alignment

arXiv:2609.22362v1 Announce Type: new Abstract: Debates about whether artificial systems can feel are often forced between two unsatisfactory positions: behavioral equivalence is treated as sufficient

safetyarxiv-cs-cl

GeoBalance: Geometry-Aware Monitoring and Reconstruction with Asymmetric Optimization for Balanced Multimodal Learning

arXiv:2609.23533v1 Announce Type: new Abstract: Multimodal classifiers can converge to modality-dominant solutions in which one modality dominates the joint prediction, suppressing the learning of oth

researcharxiv-cs-cv

HiBerNAC: Hierarchical Brain-inspired Robotic Neural Agent Collective for Disentangling Complex Manipulation

arXiv:2506.08296v3 Announce Type: replace Abstract: Recent advances in multimodal vision-language-action (VLA) models have revolutionized traditional robot learning, enabling systems to interpret visi

agentsarxiv-cs-ro

Local Ai

Learning Prognostic Variables for AI Convective Parameterizations via Symbolic Distillation

arXiv:2609.24882v1 Announce Type: new Abstract: Hybrid AI-physics climate modeling aims to improve coarse (~100km-resolution) Earth system models by learning to parameterize subgrid processes from hig

local-aiarxiv-cs-lg

LegendBench: A Diagnostic Benchmark for Legend Understanding with Counterfactual Interventions

arXiv:2609.24172v1 Announce Type: new Abstract: Legends are fundamental to chart understanding, as reliable interpretation requires correctly binding legend entries to corresponding visual marks. Whil

MM-ContextFold: Context Folding for Multimodal Agentic Retrieval

arXiv:2609.23121v1 Announce Type: new Abstract: Multimodal Agentic Retrieval (MAR) requires agents to solve complex information-seeking tasks by iteratively invoking external tools. Typical frameworks

agentsarxiv-cs-cv

MuLA-Bench: A Multilingual Long-Form Audio Understanding Benchmark via Multi-Tier Auditing

arXiv:2609.23416v1 Announce Type: cross Abstract: Long-form audio performance is often summarized by context length and aggregate accuracy, obscuring how language, evidence, and task jointly shape dif

Paragraph Boundaries Are Not White Space:Compression Depth as the Signature of Hierarchical Structure

arXiv:2609.23551v1 Announce Type: new Abstract: Standard positional encodings represent position as a one-dimensional reading-order coordinate, but reading order alone does not determine hierarchical

researcharxiv-cs-cl

Performance vs Consistency: Evaluating a Foundation Model in Lung-RADS Screening

arXiv:2609.22281v1 Announce Type: new Abstract: Foundation models have recently demonstrated strong capabilities across a wide range of medical imaging tasks. However, their performance in structured

Propose, Verify, Commit: Evidence-Grounded Memory for Long-Horizon Multi-Actor Conversations

arXiv:2609.23465v1 Announce Type: new Abstract: Long-horizon conversational memory is especially challenging in multi-actor settings, where relevant evidence is distributed across participants and con

Hardware

Scout: Open-World Species Recognition on the Edge

arXiv:2609.22897v1 Announce Type: new Abstract: Large vision-language models (VLMs) enable recognition beyond a fixed class set, but their computational demands prevent them from running on many edge

hardwarearxiv-cs-cv

Selective Commitment for Language-Guided Object Retrieval under Partial Observability

arXiv:2609.23131v1 Announce Type: new Abstract: Language-guided object retrieval under partial observability requires deciding whether to gather more evidence, interact with the scene, grasp a candida

safetyarxiv-cs-ro

Spatial Action Review: A Visual Analytics Dashboard for Auditing Language-to-Action Hand-offs in Electron Microscopy

arXiv:2609.24470v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly explored as interfaces for scientific image analysis, where a visual question-answering (VQA)

agentsarxiv-cs-cv

Applications

StateMem: Single-State Residual Memory with Adaptive Inference for Vision-Language-Action Policies

arXiv:2609.22684v1 Announce Type: cross Abstract: Memory-dependent robotic manipulation often requires later actions to use information from earlier interactions. Existing vision-language-action (VLA)

applicationsarxiv-cs-lg

Stealing profits: Spread-based temporal hierarchy forecasting for day-ahead electricity markets

arXiv:2609.23223v1 Announce Type: cross Abstract: Day-ahead electricity price forecasts support trading and storage decisions, but for battery arbitrage predicting intraday price spreads is more relev

STEVE: Stabilizing Textual Gradient-Based Prompt Optimization via Error-Driven Refinement and Regularized Verification

arXiv:2609.23716v1 Announce Type: new Abstract: Textual-gradient methods automate prompt optimization through natural-language feedback, but their iterative updates can be unstable. We identify two so

Strategy Accumulation and Guided Execution for Automated LLM Fine-Tuning

arXiv:2609.22257v1 Announce Type: cross Abstract: Producing task-specific large language models requires discovering effective training strategies through experimentation. Automated fine-tuning system

agentsarxiv-cs-cl

Streaming Deep Reinforcement Learning Finally Works

arXiv:2410.14606v3 Announce Type: replace Abstract: Learning from a stream of experience as it arrives, also known as streaming learning, is a core part of natural learning. However, reliable streamin

Structured World-State Reasoning for Agentic Robotic Search

arXiv:2609.23841v1 Announce Type: new Abstract: Long-horizon robotic search must resolve natural language against heterogeneous, incomplete, and often ambiguous evidence: textual information, prior ma

agentsarxiv-cs-ro

Tutorials

Success Leaves Detours: Learning Executable Walkthroughs for Long-Horizon Agents

arXiv:2609.22120v1 Announce Type: cross Abstract: Test-time self-evolving agents improve by reusing past experience, yet sparse-reward trajectories contain failures, loops, and detours, while summarie

tutorialsarxiv-cs-cl

Local Ai

Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation

arXiv:2407.16139v2 Announce Type: replace Abstract: Federated Learning (FL) faces challenges due to data heterogeneity, which limits the global model's performance across diverse client distributions.

local-aiarxiv-cs-lg

TEMPER: Temporal Encoder-Masked Probabilistic Ensemble Regressor for Time-Series Forecasting

arXiv:2609.23701v1 Announce Type: cross Abstract: Probabilistic forecasting requires accurate central predictions and calibrated uncertainty estimates. This paper presents TEMPER, the Temporal Encoder

Testing the Construct Validity of a Functional Valence Axis in LLM Agents

arXiv:2609.22850v1 Announce Type: new Abstract: Contrastive activation directions are often interpreted from what they decode or how strongly they steer behavior. But what evidence is sufficient to id

safetyarxiv-cs-lg

The Price of Self-Calibration: Exact Evidence Budgets and Manufactured Blind Sets in Adaptive Monitoring

arXiv:2609.23254v1 Announce Type: new Abstract: Self-calibrating monitors adapt their threshold online to guarantee a prescribed long-run false-alarm rate under arbitrary drift. We compute the price o