Search: “framework”

Quantum Reinforcement Learning for Cost and Delay Tradeoffs in Quantum Cloud Orchestration

arXiv:2609.27446v1 Announce Type: cross Abstract: Quantum cloud computing, delivered through the quantum-as-a-service (QaaS) model, provides access to quantum computing resources. However, applying un

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Reference-Based Analysis of Coherence and Diversity in Open-Ended Text Generation

DGX agent

arXiv:2609.28080v1 Announce Type: new Abstract: Evaluating open-ended text generation involves understanding how different properties of a continuation relate to its perceived quality. We present a re

safetyarxiv-cs-cl

24 Sept 2026

Regular Fourier Features for Nonstationary Gaussian Processes

arXiv:2602.23006v3 Announce Type: replace-cross Abstract: Simulating a Gaussian process requires sampling from a high-dimensional Gaussian distribution, which scales cubically with the number of sampl

researcharxiv-cs-lg

Relative Discharge Stage (RDS) Classification: A Practical Indicator of Battery Discharge Progress

model-releasesarxiv-cs-lg

arXiv:2609.27986v1 Announce Type: new Abstract: Accurate remaining discharge time (RDT) prediction is challenging in real-world battery applications because future load profiles are unknown and highly

Local Ai

Repairability of Inexact Solvers in Recursive State Estimation with Machine Learning

arXiv:2609.28425v1 Announce Type: cross Abstract: Recursive state estimation often executes approximate numerical solutions inside a feedback loop, where highly accurate local steps do not guarantee b

local-aiarxiv-cs-lg

Reporting Under Pressure: Separating Factual and Tonal Sycophancy in LLM Statistical Analysis

arXiv:2609.27756v1 Announce Type: new Abstract: Large language models are increasingly asked to analyze data and report what the results mean, a task distinct from the belief- or preference-alignment

RexDrug: Reliable Multi-Drug Combination Extraction through Reasoning-Enhanced LLMs

arXiv:2603.08166v2 Announce Type: replace Abstract: Automated Drug Combination Extraction (DCE) from large-scale biomedical literature is crucial for advancing precision medicine and pharmacological r

agentsarxiv-cs-cl

Riemannian Structure and Optimization for a Class of Low-Parametric Orthogonal Matrices

arXiv:2609.27982v1 Announce Type: cross Abstract: In this paper, we are concerned with matrices formed by block-diagonal factors interleaved with fixed permutations -- a flexible family of structured

Risk-Controlled KV-Cache Eviction: From Memory Budgets to Risk Targets

model-releasesarxiv-cs-cl

arXiv:2609.27981v1 Announce Type: new Abstract: KV-cache eviction is typically evaluated through average quality-memory trade-offs, yet a small average loss can hide requests whose utility degrades ma

Robust Adversarial Reinforcement Learning with Risk Sensitivity and Critic Consistency Regularization

arXiv:2609.27667v1 Announce Type: new Abstract: Reinforcement learning (RL) achieves strong performance in sequential decision-making but remains brittle under dynamic uncertainty and distributional s

agentsarxiv-cs-lg

Local Ai

Role of scrambling and noise in temporal information processing with quantum systems

arXiv:2505.10080v3 Announce Type: replace-cross Abstract: Scrambling quantum systems have attracted attention as effective substrates for temporal information processing. Here we consider a quantum re

local-aiarxiv-cs-lg

S2A:Semantic-to-Spatial Alignment for Alignment-Free RGB-T Salient Object Detection

arXiv:2609.27413v1 Announce Type: new Abstract: Alignment-free RGB-T salient object detection (RGB-T SOD) aims to identify salient objects from unregistered RGB and thermal image pairs without costly

safetyarxiv-cs-cv

Safe Multi-Robot Coordination via VLM-LLM Reasoning and Reachability Analysis

arXiv:2609.27816v1 Announce Type: cross Abstract: Safe coordination in heterogeneous machine-to-machine (M2M) robotic systems is challenging when robots differ in sensing capabilities, environmental a

Hardware

Scalable Subgraph Sampling via Resistance Curvature

arXiv:2609.27209v1 Announce Type: cross Abstract: Subgraph sampling reduces the training cost of large-scale graph neural networks, but sampling criteria may overlook the geometric roles of edges. We

hardwarearxiv-cs-ai

Scaling Attention Head Analysis via Gradient-Based Attribution in Context-Aware Machine Translation

arXiv:2609.28117v1 Announce Type: cross Abstract: In this paper, we introduce a gradient-based head attribution strategy where the Token-level Max-Margin loss is backpropagated to the attention maps.

Schrodinger's Code Repository: Have LLMs Learned SWE-bench or Memorized It?

arXiv:2609.27891v1 Announce Type: cross Abstract: Repository-level coding benchmarks have become the standard for evaluating coding agents, yet they inherently suffer from data leakage because they ar

ScoutNeRV: Rapid Encoding of Grid-Based Video INRs via ScoutNet

arXiv:2609.27958v1 Announce Type: new Abstract: Implicit neural representations (INRs) have emerged as a promising paradigm for video compression, providing compact neural representations with flexibl

Self-Evolving Multimedia Verification through Memory Consolidation of Contestation Experiences

arXiv:2609.27175v1 Announce Type: cross Abstract: Multimedia verification requires not only accurate decisions but also traceable evidence, reliable human correction, and safe reuse of prior experienc

Shutdown Sabotage Propensities in Multi-Agent Systems

arXiv:2609.28274v1 Announce Type: new Abstract: The final safeguard against rogue AI behavior is the human ability to shut systems down. It has been theorized that when an AI is instructed to perform

Signal2Symbol: Neuro-Symbolic Temporal Reasoning for Explainable Physiological Time-Series Anomaly Detection

arXiv:2609.26820v1 Announce Type: cross Abstract: Physiological time series such as electrocardiograms (ECG) and electroencephalograms (EEG) exhibit complex temporal structure, substantial acquisition

researcharxiv-cs-ai

Silent Failures in Agent-Tool Interaction: An Audit of ToolUniverse

arXiv:2609.26836v1 Announce Type: new Abstract: Agentic AI systems are increasingly adopting automated pipelines that integrate multiple tools. While prior research and benchmarks have studied about t

Simultaneous Latent Budget Trees for Stratified Classification

arXiv:2606.13295v3 Announce Type: replace-cross Abstract: In the era of Explainable Artificial Intelligence, there is a renewed focus on single trees for their ease of interpretation. This paper intro

researcharxiv-cs-lg

SkillGym: Internalizing Human Skills into LLMs for Real-World Problem Solving

model-releasesarxiv-cs-cl

arXiv:2609.27717v1 Announce Type: new Abstract: Human-written agent skills encode rich workflows for real-world problem solving, but are typically used as external inference-time instructions rather t

Spatiality-Frequency Domain Video Forgery Detection System Based on ResNet-LSTM-CBAM and DCT Hybrid Network

model-releasesarxiv-cs-cv

arXiv:2609.27904v1 Announce Type: new Abstract: As information technology advances, digital content has become widely adopted across diverse fields such as news broadcasting, entertainment, commerce,

Stable Neural Decoding Across Sessions via Task-Conditioned Latent Alignment for Brain-Machine Interfaces

arXiv:2609.27441v1 Announce Type: new Abstract: Achieving stable long-term neural decoding in invasive brain-machine interfaces (BMIs) remains challenging due to variations in recorded neural populati

safetyarxiv-cs-lg

StateComp: Learning When to Compress History in Long Horizon Agents

arXiv:2609.27298v1 Announce Type: new Abstract: Long-horizon agents continuously accumulate interaction history during task execution, yet the importance of past interactions changes as the agent stat

Hardware

Support-Compiled Feature Folding: More Evidence at Lower Memory Across Tabular Foundation Models

arXiv:2609.28208v1 Announce Type: new Abstract: Tabular foundation models face a feature-side scaling dilemma: full-width pairwise mixing grows quadratically with the number of columns, whereas featur

hardwarearxiv-cs-lg

Talk2Escape: Conversational Grounding for Vision-and-Language Navigation

arXiv:2609.28296v1 Announce Type: new Abstract: While Vision-and-Language Navigation (VLN) has demonstrated remarkable success, the prevailing single-turn paradigm exposes a fundamental vulnerability:

agentsarxiv-cs-ro

Tutorials

Task-Prototype Guided Flow Matching for Few-Shot Generalization in Vision-Language Robot Manipulation

arXiv:2609.27780v1 Announce Type: cross Abstract: Vision-language robot manipulation policies can follow semantic instructions, but adapting them to a new procedure from only a few demonstrations rema

tutorialsarxiv-cs-cv

ThaiTrees: Thai Syntactic Dependency Trees Across Domains

arXiv:2609.27558v1 Announce Type: new Abstract: Studying syntactic patterns in naturally occurring language requires a large parsed corpus, but manual annotation is costly and difficult to scale. Thai

researcharxiv-cs-cl

The Linear Representation Hypothesis Needs a Group Action

arXiv:2609.27158v1 Announce Type: cross Abstract: To make claims about representations that generalize beyond a particular trained model, we need to specify when two representations should count as eq

researcharxiv-cs-ai

The Past Frames the Future: Memory for Autoregressive Video Generation

arXiv:2609.28466v1 Announce Type: new Abstract: Advances in generative models have improved video fidelity, enabling long-horizon generation, interactive world modeling, and evolving visual environmen

The Path Matters: Evaluating Small Language Models Beyond Answer Accuracy in KGQA

arXiv:2609.27669v1 Announce Type: cross Abstract: Small language models (SLMs) are increasingly paired with knowledge graphs (KGs), yet end-to-end KG question answering conflates graph access, search,

Local Ai

TinyUDE: Solver-Free Universal Differential Equations on Microcontrollers via Lie-Taylor Jet Matching

arXiv:2609.26972v1 Announce Type: new Abstract: Training Universal Differential Equations (UDEs) traditionally relies on backpropagating through numerical ODE solvers, creating memory footprints far e

local-aiarxiv-cs-lg

TopoGS: Topology-Aware Anchor Feature Aggregation for Large-Scale 3D Gaussian Splatting

arXiv:2609.27868v1 Announce Type: cross Abstract: Octree-based 3D Gaussian Splatting organizes anchors into multi-level hierarchies for level-of-detail rendering, but features at different levels are

researcharxiv-cs-ai

Tutorials

Towards Efficient Reasoning: Learning Causal Shortcuts for Diffusion Language Models

arXiv:2609.28272v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) have attracted significant attention for their strong reasoning ability. However, under a bidirectional attention mecha

tutorialsarxiv-cs-cl

Track2Art: Motion-Centric Articulated Object Model Recovery from 2D Point Trackers

arXiv:2609.27675v1 Announce Type: new Abstract: Understanding articulated objects is fundamental for robotic interaction, requiring accurate rigid-part discovery and the recovery of their kinematic re

Turning Safety into Competence: Minimally Exploitable Robot Policies via Safety-Filtered Reinforcement Learning

arXiv:2609.27312v1 Announce Type: cross Abstract: Robots deployed for competitive tasks must outmaneuver their opponents without sacrificing safety. Existing approaches, including safe reinforcement l

UVU: Improving Multimodal Understanding via Vision-Language Unified Autoregressive Paradigm

arXiv:2609.27915v1 Announce Type: new Abstract: Despite remarkable advancements in multimodal large language models (MLLMs), their fine-grained visual understanding is constrained by a primary relianc

Value Mirror Descent for Reinforcement Learning

arXiv:2604.06039v2 Announce Type: replace-cross Abstract: Value iteration-type methods have been extensively studied for computing a nearly optimal value function in reinforcement learning (RL). Under

safetyarxiv-cs-lg

Visibility-Guided Structured Measure Flow for Class-Conditioned 3D Gaussian Generation

model-releasesarxiv-cs-cv

arXiv:2609.27778v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has made real-time, high-fidelity 3D rendering practical, yet turning this explicit representation into a native generative

Visual Tripwires: Anticipating Failure in Deep Vision Systems

model-releasesarxiv-cs-cv

arXiv:2609.28099v1 Announce Type: new Abstract: Deep vision systems remain vulnerable to corruption, occlusion, and distribution shift despite strong benchmark performance. Existing reliability method

VIVAS: Vitalizing Visual Perception in VLM Pre-training via Vision-language Unified Autoregressive Supervision

arXiv:2609.27948v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) demonstrate strong capabilities, they continue to suffer from a critical limitation: insufficient fine-grained visua

What Converges in the Platonic Representation Hypothesis? Structure over Geometry

arXiv:2609.27252v1 Announce Type: cross Abstract: The Platonic Representation Hypothesis suggests that increasingly capable models converge toward shared representations. Recent work narrows this clai

safetyarxiv-cs-cv

When Clients Are Orchestrated: Strategic Gradient Manipulation to Defeat Federated Learning Servers with Efficient Defense

arXiv:2609.27124v1 Announce Type: cross Abstract: Federated Learning enables decentralized model training by exchanging model updates--rather than raw data--with a central parameter server (PS). While

When Context Misleads: In-context Learning with Jurisdiction in Large Language Models

arXiv:2609.27603v1 Announce Type: cross Abstract: In-Context Learning (ICL) has become a cornerstone of modern LLM deployment. However, existing ICL post-training methods have a critical blind spot: t

When Parallel Drafter Meets Parallel Speculative Decoding

arXiv:2609.27396v1 Announce Type: new Abstract: DSpark-style parallel drafters have made speculative decoding highly effective, yet their draft phase remains serialized on the critical path of every r

researcharxiv-cs-cl

When Post-Processing Fairness Constraints Help and When They Harm: Evidence from Eight Cross-Domain Evaluations

model-releasesarxiv-cs-lg

arXiv:2609.26955v1 Announce Type: new Abstract: Fairness audits in production ML typically occur once, at deployment, on a single domain. Both fail in practice: fairness can shift after retraining or