All entries

Revisiting Spectral Representations in Generative Diffusion Models

arXiv:2609.08253v1 Announce Type: new Abstract: Diffusion models have shown remarkable performance on diverse generation tasks. Recent work finds that imposing representation alignment on the hidden s

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Revisiting Thinning Methods for Kernel Learning Problems

DGX agent

arXiv:2609.07432v1 Announce Type: new Abstract: Kernel methods are widely used because of their strong theoretical guarantees and empirical performance. However, their high computational cost limits t

researcharxiv-cs-lg

9 Sept 2026

RFS-UNet: Decoder-Conditioned High-Resolution Skip Recalibration for Bone-Selective DRR Synthesis

arXiv:2609.08044v1 Announce Type: new Abstract: Bone-selective digitally reconstructed radiograph (DRR) synthesis depends on high-resolution encoder detail, yet static skips cannot condition reuse on

researcharxiv-cs-cv

RGB Input Pipelines: Throughput, GPU Memory, and Transformation Coverage

arXiv:2609.06635v1 Announce Type: cross Abstract: An image-augmentation pipeline must deliver a complete batch before a model can use it. We compare seven input paths from five libraries, starting wit

Riemannian Optimization for Multi-Player Quantum Games on Product Unitary Manifolds

arXiv:2609.07397v1 Announce Type: cross Abstract: Quantum game theory is an extension of classical game theory that uses quantum principles in game theory. The Eisert-Wilkens-Lewenstein (EWL) quantum

agentsarxiv-cs-lg

Risk-Conditioned Fine-Tuning of Large Language Models

arXiv:2609.08064v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in settings where rare but severe harmful generations can have significant consequences. Existing

RoboCousin: Build Your Own Simulation Playground for Robust Bimanual Robotic Manipulation

arXiv:2609.08339v1 Announce Type: new Abstract: Bimanual manipulation policies require large and diverse training datasets, yet collecting demonstrations on physical robots is expensive and difficult

researcharxiv-cs-ro

RoboDreamer: Anticipatory Humanoid Locomotion with Predictive State-Space Models

arXiv:2609.07096v1 Announce Type: new Abstract: Humanoid locomotion requires control policies that remain stable under imperfect sensing while exploiting temporal context for consistent motion. We pre

RoboSense: Leveraging Robotaxi Fleets as Drive-by Sensors for Urban Traffic Monitoring

arXiv:2609.06813v1 Announce Type: new Abstract: Urban traffic monitoring plays a critical role in safety analysis, congestion management, and incident response. The growing deployment of robotaxis cre

Robots Influencing Humans to Reveal their Goals during Collaboration and Competition

arXiv:2609.05519v1 Announce Type: new Abstract: We propose a unified strategy for fast goal inference in human-robot interaction. The core idea is to drive the human toward Critical Decision Points (C

Robust conditional dimension reduction for dissimilarity data

arXiv:2609.06284v1 Announce Type: cross Abstract: Conditional dimension reduction (cDR) learns low-dimensional latent coordinates while accounting for observed covariates that represent known sources

Robust Conformal Consensus: Multi-Agent LLM-as-a-Judge Interval Evaluation with Conformal Prediction

arXiv:2609.06367v1 Announce Type: new Abstract: LLM-as-a-Judge has emerged as a promising paradigm for evaluating natural language generation. However, the uncertainty associated with such evaluations

agentsarxiv-cs-lg

Applications

Robust Decentralized Federated Distillation via Multi-Modality Knowledge Collaboration

arXiv:2609.07230v1 Announce Type: new Abstract: This paper propose a robust decentralized federated distillation method that enables clients with heterogeneous models to collaborate through prediction

applicationsarxiv-cs-lg

Local Ai

Robust Decentralized Personalized Federated Learning via Prediction-Constrained Neighborhood Collaboration

arXiv:2609.07312v1 Announce Type: new Abstract: This paper proposes a robust decentralized personalized federated learning method R-DPFL, that enables clients to reduce the impact of Byzantine attacks

local-aiarxiv-cs-lg

Robust Dynamic Expansion for Continual Learning under Backdoor Attacks via Purification and Selective Recovery

arXiv:2609.06346v1 Announce Type: new Abstract: Continual learning (CL) enables models to acquire new knowledge from sequentially arriving tasks while retaining previously learned knowledge. However,

Robust Immersive Bilateral Teleoperation of Beyond-Human-Scale Systems with Enhanced Transparency and Sense of Embodiment

arXiv:2505.14486v3 Announce Type: replace Abstract: This paper presents an immersive bilateral teleoperation framework for beyond-human-scale manipulators, combining motion/force transparency with enh

researcharxiv-cs-ro

Applications

Robust Optical Flow Computation: A Higher-Order Differential Approach

arXiv:2410.09563v2 Announce Type: replace Abstract: In the domain of computer vision, optical flow stands as a cornerstone for unraveling dynamic visual scenes. However, the challenge of accurately es

applicationsarxiv-cs-cv

Robust Vision Systems for Connected and Autonomous Vehicles: Security Challenges and Attack Vectors

arXiv:2602.09740v3 Announce Type: replace Abstract: Connected and Autonomous Vehicles (CAVs), which is critical for achieving Level-5 autonomous driving. Safe and reliable CAV navigation depends on ro

Robustness of LLM-Generated SystemVerilog Assertions to Semantics-Preserving RTL Transformations

arXiv:2609.05658v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being explored for automating SystemVerilog Assertion (SVA) generation, yet most evaluations report correc

Hardware

RoLA: Rotary-Positioned Low-Rank Linear Attention for Efficient Diffusion Transformers

arXiv:2609.06712v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) achieve strong video generation quality, but their dense spatiotemporal self-attention scales quadratically with sequence

hardwarearxiv-cs-cv

Role-Specific Predictive Geometries for Nonstationary Multivariate Graph-Signal Forecasting

arXiv:2609.06519v1 Announce Type: new Abstract: Forecasting multivariate graph signals is challenging when node-level trajectories are nonstationary but stable relations persist across nodes and featu

Rollcast: Proper-Score Gated Rolling Anchors for Adaptive Probabilistic Time-Series Forecasting

arXiv:2609.05561v1 Announce Type: cross Abstract: Rollcast is a probabilistic forecasting method for univariate time series that combines a compact set of rolling statistical anchors rather than relyi

RoMu4o: A Robotic Manipulation Unit For Orchard Operations Automating Proximal Hyperspectral Leaf Sensing

arXiv:2501.10621v2 Announce Type: replace-cross Abstract: Driven by the need to address labor shortages and meet the demands of a rapidly growing population, robotic automation has become a critical c

agentsarxiv-cs-cv

RoPE attention is an exact forward-pass gradient step with softmax intact

arXiv:2609.06685v1 Announce Type: cross Abstract: We derive an exact gradient-step representation of the RoPE-softmax forward pass. For every deterministic RoPE-softmax attention head with arbitrary a

Rotation-free Online Handwritten Character Recognition Using Linear Recurrent Units

arXiv:2602.01533v2 Announce Type: replace Abstract: Online handwritten character recognition leverages stroke order and dynamic features, which generally provide higher accuracy and robustness compare

researcharxiv-cs-cv

Routing Dense Layouts with History-Aware Offline Reinforcement Learning using LSTM

arXiv:2609.08232v1 Announce Type: cross Abstract: Detailed routing remains a dominant runtime bottleneck in physical design due to increasing complexity of design rules. Modern routers can struggle to

Run Claude Code on Ollama models with per-model context scaling and cost tracking

I've been running Claude Code as my daily driver and wanted Ollama models in the loop without giving up the harness. So I built gremlord, a small Go binary that points the unmodified claude binary at

model-releasesr-ollama

Running qwen 3.8 27B iq3 xxs on RTX 3060.

model-releasesr-localllama

Getting anywhere from 10 - 20 tps. Thinking Off . Took about 4 mins and 7 mins. Running on about 'IQ3_S - 3.4375 bpw' 37.03.960.932 I slot print_timing: id 0 | task 2665 | prompt processing, n_tokens

S^3F-Net: A Multi-Modal Approach to Medical Image Classification via Spatial-Spectral Summarizer Fusion Network

arXiv:2509.23442v2 Announce Type: replace-cross Abstract: Convolutional Neural Networks have become a cornerstone of medical image analysis due to their proficiency in learning hierarchical spatial fe

researcharxiv-cs-cv

SAEs Can Improve Unlearning: Dynamic Sparse Autoencoder Guardrails for Precision Unlearning in LLMs

arXiv:2504.08192v2 Announce Type: replace Abstract: Machine unlearning is a promising approach to improve LLM safety by removing unwanted knowledge from the model. However, prevailing gradient-based u

SAEScientist-Bench: Can AI Agents Conduct Autonomous SAE Interpretability Research?

arXiv:2609.09113v1 Announce Type: cross Abstract: While research on recursive self-improvement (RSI) has predominantly automated model training pipelines, reliable autonomous development demands a mis

Safe Consensus of Cooperative Manipulation with Hierarchical Event-Triggered Control Barrier Functions

arXiv:2603.06356v2 Announce Type: replace Abstract: Cooperative transport and manipulation of heavy or bulky payloads by multiple manipulators requires coordinated formation tracking, while simultaneo

Safe Task Planning with Long-Term Graph Memory for Embodied Agents

model-releasesarxiv-cs-ro

arXiv:2609.08444v1 Announce Type: new Abstract: Large language models (LLMs) and vision-language models (VLMs) have significantly advanced zero-shot task planning for embodied agents. However, most LL

SAFEGuard: Detect Optimization-Based Jailbreak Attacks Through Harmful Semantic Analysis and Fluency Measurement

arXiv:2609.05850v1 Announce Type: new Abstract: Despite the significant efforts devoted to aligning large language models (LLMs) with human values and ensuring safe deployment, recent work has reveale

SAFER-Activities: A Dataset for Smart Assessment of Fall Events and Routine Activities

arXiv:2609.08038v1 Announce Type: new Abstract: Smart healthcare monitoring systems require precise action recognition to ensure well-being and timely intervention in critical situations such as falls

SAFIRE: Safety-Critical Benchmark for Fine-grained Fire and Smoke Understanding in Multimodal LLMs

arXiv:2609.07823v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) show strong progress on vision-language tasks, yet their reliability in safety-critical settings remains undere

Sam said that at the Senate in 2023, too; i was there, right next to him. and then he quietly lobbied against the EU AI Act. can anybody eve…

Sam said that at the Senate in 2023, too; i was there, right next to him. and then he quietly lobbied against the EU AI Act. can anybody ever take him at his word? NEWS: OpenAI told congressional offi

safetygary-marcus--x

Local Ai

SAM3-O2D2: Zero-Shot Object Out-of-Distribution Detection by Object Class Prompting of the SAM3-Image Model

arXiv:2609.08281v1 Announce Type: new Abstract: Object detectors have shown remarkable performance in various fields, among these medical imaging, surveillance, and autonomous driving. However, they a

local-aiarxiv-cs-cv

@sama Maybe. Or maybe this isn’t even an isolated incident, just like the Hugging Face incident wasn’t quite a one-off:

@sama Maybe. Or maybe this isn’t even an isolated incident, just like the Hugging Face incident wasn’t quite a one-off: BREAKING: OpenAI might have stolen another major proof. In a detailed Mastodon p

safetygary-marcus--x

Scalability Analysis of Distributed Kolmogorov-Arnold Network Training on High-Performance Computing Systems

arXiv:2609.07740v1 Announce Type: cross Abstract: Kolmogorov-Arnold Networks (KANs) replace the fixed activation functions and linear weights of Multi-Layer Perceptrons (MLPs) with learnable univariat

Scaling 3D Generative Priors to Large-Scale Scene Meshes from Multi-View Images

arXiv:2609.06385v1 Announce Type: new Abstract: Pretrained 3D generative models produce detailed geometry and appearance but are primarily designed for object-centric generation within a limited spati

safetyarxiv-cs-cv

Scaling Optimal Classification Trees via Adaptive Feature and Sample Reduction

arXiv:2609.05826v1 Announce Type: new Abstract: Dynamic programming for optimal classification trees becomes computationally expensive as the numbers of features and training samples increase. We deve

Scene Graph-Driven Haptic Feedback for Safety Enhancement in Robotic Ophthalmic Surgery via Physically Simulated iOCT

arXiv:2609.07857v1 Announce Type: cross Abstract: Robotic ophthalmic surgery offers high precision but introduces a 'sensory gap' by decoupling the surgeon from their instrument, resulting in a loss o

safetyarxiv-cs-cv

SceneMosaic: Efficient and Diverse Simulation-Ready Scene Generation via Hybrid Agentic Layout Evolution

arXiv:2609.05594v1 Announce Type: new Abstract: Diverse and simulation-ready indoor scenes are essential for interactive entertainment and embodied AI, yet their scalable generation remains challengin

agentsarxiv-cs-cv

Scientists at frontier AI labs have unique insight into the most advanced models, often seeing the associated risks months before models are…

model-releasesyoshua-bengio--x

Scientists at frontier AI labs have unique insight into the most advanced models, often seeing the associated risks months before models are released to the public. Their perspective is vital for keep

SciFigure2Code: An AI-Reconstructed Benchmark for Scientific Figure-to-Code

arXiv:2609.08155v1 Announce Type: new Abstract: Scientific figures are the interface through which research claims are inspected and reused, but final published panels rarely expose the data or plotti

SCoCaT: Success Conditioned Constrained Reinforcement Learning for Spacecraft Docking

arXiv:2609.06061v1 Announce Type: new Abstract: Termination-based constrained reinforcement learning is attractive for safety-critical robotic deployments: it avoids online optimization at inference,

SeaCausal-FL: Federated Fuzzy Causal Learning for Maritime IoT Fault Diagnosis and Counterfactual Reasoning

arXiv:2609.06257v1 Announce Type: new Abstract: Reliable marine-engine fault diagnosis in maritime IoT is challenged by distributed data ownership, heterogeneous fault distributions, and continuously