Search: “persistence”

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

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Local Ai

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

DGX agent

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

22 Sept 2026

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?

model-releasesarxiv-cs-cv

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

model-releasesarxiv-cs-cv

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

model-releasesarxiv-cs-cv

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

Tool-Augmented On-Policy Distillation for LLM Domain Adaptation in Sequence-Based Omics Tasks

arXiv:2609.23435v1 Announce Type: cross Abstract: Multi-omics sequences contain complex biological patterns, yet deciphering their mechanisms for automated scientific discovery remains challenging. As

VISTA: An Attention-Based Multi-Agent Reinforcement Learning Architecture for Space Situational Awareness Sensor Tasking

arXiv:2609.23875v1 Announce Type: new Abstract: The rapid growth of resident space objects is increasing the complexity of space situational awareness sensor tasking, challenging classical optimizatio

agentsarxiv-cs-lg

Watching Quantum Models Think: Hilbert-Space Interpretability in Quantum Transformer Blocks

arXiv:2609.23016v1 Announce Type: cross Abstract: Deep learning models are powerful but opaque. As quantum machine learning matures, the field faces a defining choice: build quantum models that are eq

What Is The Political Content in LLMs' Pre- and Post-Training Data?

arXiv:2509.22367v3 Announce Type: replace Abstract: Large language models (LLMs) reflect politically-slanted opinions in their generated text. Even though it is widely assumed that model behavior stem

researcharxiv-cs-cl

When Is Availability-Aware Training Worth It? A Benchmark and Empirical Study of Interruption-Resilient Optimization Under Predictable Compute Schedules

arXiv:2609.22087v1 Announce Type: cross Abstract: Training under non-stationary but predictable compute availability (satellites under eclipse, duty-cycled edge devices, power-capped datacenters) is o

Attention-Aware Routing: Coupling Routing and Attention in MoEs

arXiv:2609.20974v1 Announce Type: new Abstract: In Mixture-of-Experts language models, the router typically selects and weights experts based on the token's hidden state, utilizing limited contextual

researcharxiv-cs-ai

Beyond Gaussian Worlds: Latent Geometry Matters for JEPAs

arXiv:2609.21656v1 Announce Type: new Abstract: Recent Joint-Embedding Predictive Architectures (JEPAs) prevent representation collapse by constraining learned representations to follow a prescribed t

safetyarxiv-cs-lg

CASE: Contrastive Activation for Class-Sensitive Explanations

arXiv:2506.07327v4 Announce Type: replace Abstract: Saliency methods are widely used to visualize which input features are deemed relevant to a model's prediction. However, their visual plausibility c

researcharxiv-cs-cv

CIBuzzBench: A Benchmark for Cross-Lingual Understanding of Chinese Internet Buzzwords

model-releasesarxiv-cs-ai

arXiv:2609.21722v1 Announce Type: cross Abstract: Chinese social media has generated a vast and continually evolving lexicon of internet buzzwords whose meanings are often non-literal and deeply roote

CoLearn: An Agentic Tutor that Learns its Learner in a Human--AI Co-Learning Loop

arXiv:2609.21154v1 Announce Type: new Abstract: Good tutoring adapts to the individual: it tracks what a learner knows, notices why they go wrong, and asks the next question that will help most. Most

agentsarxiv-cs-cl

Compact but Moving: Intervention-Relevant Geometry in Recurrent World Models

model-releasesarxiv-cs-ro

arXiv:2609.21787v1 Announce Type: new Abstract: Learned world models may have compact interventions even when their recurrent state is high-dimensional, but it is unclear what happens to such a correc

Do Personality-Tuned LLMs Make Better Social Agents?

model-releasesarxiv-cs-ai

arXiv:2609.21857v1 Announce Type: cross Abstract: LLMs are increasingly used in social simulations for socially interactive agents and robots, offering more flexibility than rule-based systems. Howeve

Duty Factor Predicts Robust Constrained Quadrupedal Locomotion Across Gait Types

model-releasesarxiv-cs-ro

arXiv:2609.22073v1 Announce Type: new Abstract: Quadrupedal robots are increasingly deployed in environments where locomotion must remain robust to disturbances and constrained terrain. Gait type, suc

Dynamics-Induced Commitment in Learning-Based Robotic Penalty Kicks

arXiv:2609.21100v1 Announce Type: new Abstract: Learning in robotic games is constrained not only by strategic information but also by what the body can still execute. We study this coupling in a hier

researcharxiv-cs-ro

Evaluating In-Context Learning and Retrieval Strategies for Devanagari Post-OCR Correction

arXiv:2609.21595v1 Announce Type: new Abstract: In-context learning using Large Language Models (LLMs) offers a compelling path to training-free post-OCR correction, yet its effectiveness for Devanaga

Generative inversion for early ranking of competing geologic interpretations

arXiv:2609.20978v1 Announce Type: new Abstract: High-consequence subsurface decisions are often made under severe data scarcity. Experts may arrive at competing interpretations of the same subsurface

How Many Humans Is a Judge Panel Worth?

arXiv:2609.21277v1 Announce Type: new Abstract: How many human judgments does a panel of language models represent? The answer depends on what is matched. We audit categorical judge panels against emp

researcharxiv-cs-cl