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arXiv:2605.09939v1 Announce Type: new Abstract: Autonomous and safe navigation of tractor-trailer systems requires accurate, real-time collision avoidance and dynamically feasible control, particularl

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No Mean Feat: Simple, Strong Baselines for Context Compression

DGX agent

arXiv:2510.20797v2 Announce Type: replace-cross Abstract: Context compression reduces Transformer inference costs by replacing lengthy inputs with shorter pre-computed representations. It carries sign

researcharxiv-cs-ai

12 May 2026

Hardware

Non-Monotonic Latency in Apple MPS Decoding: KV Cache Interactions and Execution Regimes

arXiv:2605.08913v1 Announce Type: cross Abstract: Autoregressive inference is typically assumed to scale predictably with decoding length, and key-value (KV) caching is widely regarded as a universall

hardwarearxiv-cs-cl

Hardware

Not All Thoughts Need HBM: Semantics-Aware Memory Hierarchy for LLM Reasoning

arXiv:2605.09490v1 Announce Type: new Abstract: Reasoning LLMs produce thousands of chain-of-thought tokens whose KV cache must reside in scarce GPU HBM. The dominant response -- permanently evicting

hardwarearxiv-cs-cl

Not Blind but Silenced: Rebalancing Vision and Language via Adversarial Counter-Commonsense Equilibrium

arXiv:2605.10676v1 Announce Type: new Abstract: During MLLM decoding, attention often abnormally concentrates on irrelevant image tokens. While existing research dismisses this as invalid noise and fo

Agents

NyayaAI: An AI-Powered Legal Assistant Using Multi-Agent Architecture and Retrieval-Augmented Generation

arXiv:2605.10155v1 Announce Type: new Abstract: Legal information in India remains largely inaccessible due to the complexity of legal language and the sheer volume of legal documentation involved in

agentsarxiv-cs-cl

On the Overscaling Curse of Parallel Thinking: System Efficacy Contradicts Sample Efficiency

arXiv:2601.21619v2 Announce Type: replace-cross Abstract: Parallel thinking improves LLM reasoning through multi-path sampling and aggregation. In standard evaluations, due to a lack of sample-specifi

applicationsarxiv-cs-ai

Online Sharp-Calibrated Bayesian Optimization

arXiv:2605.10572v1 Announce Type: new Abstract: Bayesian optimization (BO) is a widely used framework for optimizing expensive black-box functions, commonly based on Gaussian process (GP) surrogate mo

applicationsarxiv-cs-lg

Only Train Once: Uncertainty-Aware One-Class Learning for Face Authenticity Detection

arXiv:2605.10040v1 Announce Type: new Abstract: The rapid evolution of generative paradigms has enabled the creation of highly realistic imagery, which escalating the risks of identity fraud and the d

Open Ontologies: Tool-Augmented Ontology Engineering with Stable Matching Alignment

arXiv:2605.09184v1 Announce Type: new Abstract: We present Open Ontologies, an open-source ontology engineering system implemented in Rust that integrates LLM-driven construction with formal OWL reaso

Optimal Regret for Single Index Bandits

arXiv:2605.09454v1 Announce Type: cross Abstract: We study the extit{single-index bandit} problem, where rewards depend on an unknown one-dimensional projection of high-dimensional contexts through an

researcharxiv-cs-lg

Optimizer-Induced Mode Connectivity: From AdamW to Muon

arXiv:2605.09991v1 Announce Type: new Abstract: Mode connectivity has been widely studied, yet the role of the optimizer remains underexplored. We revisit it through optimizer-induced implicit regular

Optimizing Server Placement for Vertical Federated Learning in Dynamic Edge/Fog Networks

arXiv:2605.09813v1 Announce Type: cross Abstract: We investigate the control and optimization of vertical federated learning (VFL), a class of distributed machine learning (ML) methods in which edge/f

researcharxiv-cs-lg

OZ-TAL: Online Zero-Shot Temporal Action Localization

arXiv:2605.09976v1 Announce Type: new Abstract: Online Temporal Action Localization (On-TAL) aims to detect the occurrence time and category of actions in untrimmed streaming videos immediately upon t

PA-RNet: Perturbation-Aware Residual Network for Robust Multimodal Time Series Forecasting

arXiv:2508.04750v2 Announce Type: replace Abstract: In real-world applications, multimodal time-series forecasting faces a key challenge: textual information is often useful but unreliable. Auxiliary

applicationsarxiv-cs-lg

Tutorials

PaMoSplat: Part-Aware Motion-Guided Gaussian Splatting for Dynamic Scene Reconstruction

arXiv:2605.10307v1 Announce Type: new Abstract: Dynamic scene reconstruction represents a fundamental yet demanding challenge in computer vision and robotics. While recent progress in 3DGS-based metho

tutorialsarxiv-cs-cv

PATRA: Pattern-Aware Alignment and Balanced Reasoning for Time Series Question Answering

arXiv:2602.23161v2 Announce Type: replace Abstract: Time series reasoning demands both the perception of complex dynamics and logical depth. However, existing LLM-based approaches exhibit two limitati

PersonaTeaming: Supporting Persona-Driven Red-Teaming for Generative AI

arXiv:2605.05682v2 Announce Type: replace-cross Abstract: Recent developments in AI safety research have called for red-teaming methods that effectively surface potential risks posed by generative AI

PGID: Progressive Guided Inversion and Denoising for Robust Watermark Detection

arXiv:2605.09319v1 Announce Type: new Abstract: With the proliferation of AI-generated images, digital watermarking has become an essential safeguard for protecting intellectual property and mitigatin

Phases of Muon: When Muon Eclipses SignSGD

arXiv:2605.09552v1 Announce Type: cross Abstract: Recently, Muon and related spectral optimizers have demonstrated strong empirical performance as scalable stochastic methods, often outperforming Adam

researcharxiv-cs-lg

PhysEDA: Physics-Aware Learning Framework for Efficient EDA With Manhattan Distance Decay

arXiv:2605.10547v1 Announce Type: new Abstract: Electronic design automation (EDA) addresses placement, routing, timing analysis, and power-integrity verification for integrated circuits. Learning met

safetyarxiv-cs-lg

Local Ai

Physical probes expose and alleviate chemical-environment collapse in molecular representations

arXiv:2605.10429v1 Announce Type: cross Abstract: Nuclear magnetic resonance (NMR) spectroscopy provides an experimental readout of local chemical environments, but its use in molecular representation

local-aiarxiv-cs-ai

Local Ai

PoHAR: Understanding Hyperlocal Human Activities with Pollution Sensor Networks

arXiv:2605.09434v1 Announce Type: cross Abstract: Low-cost air quality sensors are becoming ubiquitous in our daily lives as public awareness of air pollution continues to grow, and people take measur

local-aiarxiv-cs-lg

Position: Life-Logging Video Streams Make the Privacy-Utility Trade-off Inevitable

arXiv:2605.10404v1 Announce Type: new Abstract: With the growing prevalence of always-on hardware such as smart glasses, body cameras, and home security systems, life-logging visual sensing is becomin

Positional Encoding via Token-Aware Phase Attention

arXiv:2509.12635v3 Announce Type: replace-cross Abstract: We prove under practical assumptions that Rotary Positional Embedding (RoPE) introduces an intrinsic distance-dependent bias in attention scor

Positional LSH: Binary Block Matrix Approximation for Attention with Linear Biases

arXiv:2605.09472v1 Announce Type: new Abstract: Positional encoding in transformers is commonly implemented through positional embeddings, attention masks, or bias terms, but formal connections betwee

safetyarxiv-cs-lg

PowerStep: Memory-Efficient Adaptive Optimization via ell_p-Norm Steepest Descent

arXiv:2605.10335v1 Announce Type: cross Abstract: Adaptive optimizers, most notably Adam, have become the default standard for training large-scale neural networks such as Transformers. These methods

Practical Wi-Fi-based Motion Recognition Under Variable Traffic Patterns

arXiv:2605.08308v1 Announce Type: cross Abstract: Wi-Fi sensing detects human motions and activities by analysing the channel state information (CSI) derived from Wi-Fi transmissions. However, the imp

Privacy-Aware Video Anomaly Detection through Orthogonal Subspace Projection

arXiv:2605.08651v1 Announce Type: cross Abstract: Video anomaly detection (VAD) systems often prioritize accuracy while overlooking privacy concerns, limiting their suitability for real-world deployme

Probability-Flow Distillation: Exact Wasserstein Gradient Flow for High-Fidelity 3D Generation

arXiv:2605.09071v1 Announce Type: new Abstract: Score Distillation Sampling (SDS) and its variants have been widely used for text-to-3D generation by distilling 2D image diffusion priors. However, the

ProteinOPD: Towards Effective and Efficient Preference Alignment for Protein Design

arXiv:2605.10189v1 Announce Type: cross Abstract: Designing proteins with desired functions or properties represents a core goal in synthetic biology and drug discovery. Recent advances in protein lan

Q-learning with Adjoint Matching

arXiv:2601.14234v3 Announce Type: replace-cross Abstract: We propose Q-learning with Adjoint Matching (QAM), a novel TD-based reinforcement learning (RL) algorithm that tackles a long-standing challen

Rapid Forest Fuel Load Estimation via Virtual Remote Sensing and Metric-Scale Feed-Forward 3D Reconstruction

arXiv:2605.10789v1 Announce Type: new Abstract: Accurate quantification of forest coverage and combustible biomass (fuel load) is critical for wildfire risk assessment and ecosystem management. Howeve

Local Ai

RAwR: Role-Aware Rewiring via Approximate Equitable Partition

arXiv:2605.09457v1 Announce Type: cross Abstract: While Graph Neural Networks (GNNs) have demonstrated significant efficacy in node classification tasks, where predictions rely on local neighborhood i

local-aiarxiv-cs-ai

Tutorials

Reasoning Trajectories for Socratic Debugging of Student Code: From Misconceptions to Contradictions and Updated Beliefs

arXiv:2511.00371v2 Announce Type: replace Abstract: In Socratic debugging, instructors guide students towards identifying and fixing a bug on their own, instead of providing the bug fix directly. Most

tutorialsarxiv-cs-cl

Rebellious Student: Reversing Teacher Signals for Reasoning Exploration with Self-Distilled RLVR

arXiv:2605.10781v1 Announce Type: cross Abstract: Self-distillation has emerged as a powerful framework for post-training LLMs, where a teacher conditioned on extra information guides a student withou

researcharxiv-cs-cl

Reducing Annotation Burden for Femoral Cartilage Segmentation in Knee MRI via Cross-Sequence Transfer Learning

arXiv:2605.09067v1 Announce Type: new Abstract: Purpose: To develop and evaluate cross-sequence transfer learning for automatic femoral cartilage segmentation, testing bidirectional transfer between d

Reflective Prompted Policy Optimization: Trajectory-Grounded Revision and Salience Bias

arXiv:2605.08315v1 Announce Type: new Abstract: Existing LLM-based policy optimizers see only scalar rewards: that a policy scored 0.45, but not whether the agent got stuck in a loop, fell into a hole

safetyarxiv-cs-lg

RIR-Former: Coordinate-Guided Transformer for Continuous Reconstruction of Room Impulse Responses

arXiv:2602.01861v3 Announce Type: replace-cross Abstract: Room impulse responses (RIRs) are essential for many acoustic signal processing tasks, yet measuring them densely across space is often imprac

applicationsarxiv-cs-lg

Robust Building Damage Detection in Cross-Disaster Settings Using Domain Adaptation

arXiv:2603.14694v2 Announce Type: replace-cross Abstract: Rapid structural damage assessment from remote sensing imagery is essential for timely disaster response. Within human-machine systems (HMS) f

Robust Probabilistic Shielding for Safe Offline Reinforcement Learning

arXiv:2605.10293v1 Announce Type: cross Abstract: In offline reinforcement learning (RL), we learn policies from fixed datasets without environment interaction. The major challenges are to provide gua

RubricEM: Meta-RL with Rubric-guided Policy Decomposition beyond Verifiable Rewards

arXiv:2605.10899v1 Announce Type: new Abstract: Training deep research agents, namely systems that plan, search, evaluate evidence, and synthesize long-form reports, pushes reinforcement learning beyo

safetyarxiv-cs-cl

Safe Exploration for Nonlinear Processes Using Online Gaussian Process Learning

arXiv:2605.09772v1 Announce Type: cross Abstract: This paper proposes a safe data-driven control framework for nonlinear systems with partially known dynamics. The method ensures stability and constra

safetyarxiv-cs-ro

Scalable Inspection Planning via Flow-based Mixed Integer Linear Programming

arXiv:2603.16593v2 Announce Type: replace Abstract: Inspection planning is concerned with computing the shortest robot path to inspect a given set of points of interest (POIs) using the robot's sensor

applicationsarxiv-cs-ro

Agents

ScholarPeer: A Context-Aware Multi-Agent Framework for Automated Peer Review

arXiv:2601.22638v2 Announce Type: replace-cross Abstract: The exponential growth of machine learning submissions has strained the traditional peer review process, resulting in slow feedback loops for

agentsarxiv-cs-ai

SeasonScapes: Learning Large-scale Re-lightable 3D Landscapes with Seasonal Variation from Sparse Webcams

arXiv:2605.09039v1 Announce Type: new Abstract: We introduce SeasonScapes framework and a the SeasonScapes dataset: Swiss Sparse-view Mountain Scenes with Seasonal Changes that covers over 50 km x 60

Segment Anything with Robust Uncertainty-Accuracy Correlation

arXiv:2605.10603v1 Announce Type: new Abstract: Despite strong zero-shot performance, SAM is unreliable under domain shift due to Mask-level Confidence Confusion (MCC), where a single IoU-based mask s

safetyarxiv-cs-cv

Semantic Voting: Execution-Grounded Consensus for LLM Code Generation

arXiv:2605.08680v1 Announce Type: cross Abstract: LLM code-generation pipelines often sample multiple candidates and select one final answer without access to a complete oracle. Existing pipelines mix