Search: “inference”

Domain-adaptive Zero-Shot Image Enhancement via Locality-Constrained Diffusion Guidance

arXiv:2609.35289v1 Announce Type: new Abstract: Denoising Diffusion Probabilistic Models have shown remarkable performance in unconditional image generation. In order to generate images with desired s

local-aiarxiv-cs-cv

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DP-Rec: Towards Dynamic Patching for Efficient Long-Sequence Recommendation

DGX agent

arXiv:2609.32215v1 Announce Type: new Abstract: Transformers have redefined sequential recommendation by effectively modeling dynamic user behaviors and long-range dependencies. However, they remain i

researcharxiv-cs-lg

29 Sept 2026

DR-net-Mamba: Selective State-Space Modeling for Long-Range ECG Time-Series Denoising

arXiv:2609.35634v1 Announce Type: new Abstract: Electrocardiogram (ECG) recordings are corrupted by non-stationary noise sources that degrade diagnostic reliability, particularly in ambulatory and lon

local-aiarxiv-cs-lg

DRAM: Delta-rule Recurrent Associative Memory for Robot Manipulation Policies

arXiv:2609.32453v1 Announce Type: new Abstract: Robotic manipulation is inherently history-dependent, yet most pretrained robotic policies condition on only the current observation or a short temporal

safetyarxiv-cs-ro

Dynamic Image Prompt Adapter for Scalable Zero-shot Personalized Text-to-Image Generation

arXiv:2512.09814v2 Announce Type: replace Abstract: Personalized Text-to-Image (PT2I) generation aims to produce customized images based on reference images. A prominent interest pertains to the integ

E-WAVE: Event-based Continuous Optical Flow via Warping-Aligned Visual Encoding

arXiv:2609.34346v1 Announce Type: new Abstract: Temporally dense optical flow is essential for dynamic perception in immersive VR/AR systems, where rapid head, hand, and object motion must be continuo

EdgeVLN: Runtime-Aware Deployment Ready Quantized Vision Language Navigation Model

arXiv:2609.35570v1 Announce Type: cross Abstract: Vision-language navigation (VLN) models perform well but target compute-rich platforms, limiting deployment on memory- and power-constrained robotic e

EEGAgentBench: Benchmarking LLM Agents on Short- and Long-Horizon EEG Analysis

arXiv:2609.31632v1 Announce Type: new Abstract: Electroencephalography (EEG) analysis is evolving from short-segment classification toward long-horizon interpretation that demands iterative evidence a

Agents

EMPIRIC: Experiment-Driven Learning of Residual World Models for Robot Planning

arXiv:2609.35047v1 Announce Type: cross Abstract: A robot should be able to learn through experiments how unfamiliar objects behave and interact, then plan with that knowledge. It need not start from

agentsarxiv-cs-lg

ENet-GP: Unified Document Image Restoration

arXiv:2609.33758v1 Announce Type: new Abstract: Reliable document digitization in uncontrolled capture settings is challenging because real images exhibit multiple interacting degradations rather than

Environment-Conditioned Tail Reweighting for Invariant Learning under Mixed Shifts

arXiv:2601.22944v3 Announce Type: replace Abstract: Out-of-distribution generalization becomes challenging when spurious correlations vary across environments while difficult or underrepresented sampl

applicationsarxiv-cs-lg

Estimate, Don't Imitate: Reusing Differentiable State-Based Policies for Visuomotor Control

arXiv:2609.34018v1 Announce Type: cross Abstract: Simulation-trained manipulation policies can exploit privileged state information to learn effective contact-rich behaviours, but deployment requires

eval-unlearn: Benchmarking unlearning in Text-to-Image Diffusion Models

arXiv:2609.35269v1 Announce Type: cross Abstract: The rising number of concept unlearning techniques for text-to-image (T2I) diffusion models has produced a fragmented evaluation landscape. Methods ar

eVGGT: An Efficient Geometry-Aware Vision Encoder for Visuomotor Policies

arXiv:2509.15880v2 Announce Type: replace Abstract: Geometry-grounded vision models, such as VGGT, have emerged as robust visual encoders, providing essential geometric priors for robotic manipulation

safetyarxiv-cs-ro

Hardware

Facial classification Using Hybrid Quantum Machine Learning

arXiv:2609.31915v1 Announce Type: new Abstract: Hybrid quantum methods have received limited study for resource-constrained facial biometrics. We present a hybrid quantum-classical facial recognition

hardwarearxiv-cs-cv

Fast and Precise Learned Charged-Particle Trajectory Regression at the Large Hadron Collider

arXiv:2609.32479v1 Announce Type: new Abstract: We propose a training recipe that treats charged-particle trajectory parameter regression on high-energy physics detector data as a sequence-modeling ta

Fast-Slow Thinking RM: Efficient Integration of Scalar and Generative Reward Models

arXiv:2603.20212v2 Announce Type: replace-cross Abstract: Reward models (RMs) are critical for aligning Large Language Models via Reinforcement Learning from Human Feedback (RLHF). While Generative Re

Fewer Tokens, More Self-Teaching: On-Policy Self-Distillation for Extreme Visual Token Reduction

arXiv:2609.32353v1 Announce Type: new Abstract: Visual token reduction is an effective way to accelerate multimodal large language models (MLLMs), but performance deteriorates rapidly under extremely

safetyarxiv-cs-cv

Hardware

Fill2SR: Repurposing Inpainting Diffusion Transformers for Real-World Super-Resolution

arXiv:2609.33582v1 Announce Type: new Abstract: Recent real-world image super-resolution (SR) methods often adapt text-to-image (T2I) backbones with ControlNet-style branches or spatial conditioning t

hardwarearxiv-cs-cv

FloodDiffusion 2: Efficient and Path Controllable Streaming Motion Generation

arXiv:2609.33167v1 Announce Type: new Abstract: We present FloodDiffusion 2 (FD2), an efficient and controllable framework that builds upon FloodDiffusion (FD1), a state-of-the-art streaming motion ge

FlowTool: Controlling Tool Parameter in Image Retouching via Flow Matching

arXiv:2609.35673v1 Announce Type: new Abstract: Tool-based image editing (image retouching) is commonly formulated with autoregressive multimodal large language models (MLLMs) that sequentially genera

Focus and Supplement: Dual-Enhanced Vision Transformer for Multi-Class Anomaly Classification

arXiv:2609.33353v1 Announce Type: new Abstract: Multi-class anomaly classification in industrial vision remains challenging due to noisy/incomplete anomaly representations and the unknown number of an

Forest-Guided Semantic Transport for Label-Supervised Manifold Alignment

arXiv:2602.00974v2 Announce Type: replace Abstract: Label-supervised manifold alignment bridges the gap between unsupervised and correspondence-based paradigms by leveraging shared label information t

FORGE: Form-Optimal Routing of Grounded Evidence for Frozen LLM Agents

arXiv:2609.34358v1 Announce Type: new Abstract: In agentic AI systems, frozen foundation models are increasingly deployed as closed-weight API endpoints, making downstream adaptation possible only thr

from our blog post on how we made Claude faster: https://claude.dev/blog/how-we-made-claude-ai-faster/

Claude.ai achieved roughly a three‑fold speed increase in just two weeks by implementing targeted engineering optimisations. The blog post on claude.dev explains the key changes—such as streamlined co

model-releasesthariq--x

FSS-UBrain: Multi-region Few-Shot Brain Tumor MRI Segmentation

arXiv:2609.32273v1 Announce Type: new Abstract: Accurate delineation of whole tumor (WT), tumor core (TC), and enhancing tumor (ET) from multimodal magnetic resonance imaging remains challenging under

Future Information-Directed Sampling for Bayesian Nonstationary Bandits

arXiv:2609.33981v1 Announce Type: new Abstract: Exploration--exploitation is a central trade-off in bandit learning. While classical algorithms such as upper confidence bound methods and Thompson Samp

FutureDuet: Decoupling Observation Access from Future Supervision in World Action Models

arXiv:2609.34362v1 Announce Type: new Abstract: World Action Models (WAMs) augment robot action generation with future visual supervision. Existing WAMs commonly fuse main and wrist observations into

local-aiarxiv-cs-ro

GeoCR: Learning a Generalist Cloud Removal Prior from Heterogeneous Observations

arXiv:2609.32510v1 Announce Type: new Abstract: Cloud removal methods are typically specialized to individual datasets and input configurations, limiting reuse across sensors, spectral bands, and obse

Goal-Conditioned Supervised Learning for Multi-Objective Recommendation

arXiv:2412.08911v4 Announce Type: replace Abstract: Multi-objective learning endeavors to concurrently optimize multiple objectives using a single model, aiming to achieve high and balanced performanc

Groupwise Selective State-Space Filtering for Accurate and Streaming Action Boundary Detection

arXiv:2609.33400v1 Announce Type: new Abstract: Action boundary detection partitions untrimmed video into intervals without assigning action classes. We present a boundary-detection adapter operating

GuardPIBT: Counterfactually Gated Neural Guidance for Ultra-Large-Scale 3D Multi-Agent Path Finding

arXiv:2609.35267v1 Announce Type: new Abstract: Large-scale 3D multi-agent path finding becomes increasingly difficult under dense traffic. Priority Inheritance with Backtracking (PIBT) scales well, b

local-aiarxiv-cs-ro

Agents

GUIDE-FBO: Guidance via Uncertainty Intervention and Distributional Exchange for Federated Bayesian Optimization

arXiv:2609.35038v1 Announce Type: cross Abstract: Federated Bayesian Optimization (FBO) enables distributed agents to collaboratively optimize expensive black-box objectives without sharing raw local

agentsarxiv-cs-lg

Hardware-Aware Features for CUTLASS Kernel Selection

arXiv:2609.35587v1 Announce Type: new Abstract: GPU libraries such as CUTLASS expose tens of thousands of semantically equivalent kernels for a single operation, making exhaustive autotuning expensive

HGPTrans: Hierarchical Graph-Pooling Transolver for Automotive Aerodynamic Drag Coefficient Prediction

arXiv:2609.31765v1 Announce Type: new Abstract: Accurate and rapid prediction of the aerodynamic drag coefficient (C_D) is essential for vehicle design, particularly during early-stage styling iterati

local-aiarxiv-cs-cv

Humanoid Loco-Manipulation With Discrete VLA Model

model-releasesarxiv-cs-ro

arXiv:2609.35709v1 Announce Type: new Abstract: Vision-language-action (VLA) models using discrete action tokens have proven effective for controling robotic arms on manipulation tasks. For a humanoid

In-Token Learning for High-Fidelity Image Restoration via Diffusion Transformers

arXiv:2609.33523v1 Announce Type: new Abstract: We present In-Token Learning, an image restoration framework that adapts a pretrained diffusion transformer using conditional rectified flow matching. C

Integrating Language Models into Listened and Imagined Speech Decoding from MEG

arXiv:2609.31997v1 Announce Type: new Abstract: Decoding imagined speech is an important goal for brain-computer interfaces but remains challenging due to weak neural responses, low signal-to-noise ra

JET: Justification Evaluation in Transformer

arXiv:2609.33874v1 Announce Type: new Abstract: JET uses pretrained language and vision-language models to select among a finite set of answers without additional training. It evaluates candidate like

local-aiarxiv-cs-lg

Just MLPs: Efficient Visual State Reconstruction for Multimodal Language Models

arXiv:2609.34972v1 Announce Type: new Abstract: Long visual token sequences often account for a substantial fraction of the computational overhead in multimodal large language models~(MLLMs). Existing

Agents

Kafila: Serving Large Language Models on a Trusted Set of Heterogeneous Commodity Machines

arXiv:2609.34045v1 Announce Type: cross Abstract: Between them, the members of a research group or a circle of friends own several consumer computers, none large enough to run a capable large language

agentsarxiv-cs-lg

KeyRec: Bounded Visual Memory for Streaming and Long-Video Understanding

arXiv:2609.32182v1 Announce Type: new Abstract: Vision-language models are increasingly used to understand long videos and continuous streams. However, dense visual tokens accumulate with video durati

KiT: A Foundation Model for Financial Time-Series Forecasting using DiffusionTransformers

arXiv:2609.34507v1 Announce Type: cross Abstract: Financial candlestick forecasting is fundamental to quantitative investment, yet it remains exceptionally challenging due to extremely low signal-to-n

Knowledge-Driven XRD Phase Identification via Multi-View Retrieval and Explanation

arXiv:2609.31888v1 Announce Type: cross Abstract: X-ray diffraction (XRD) is a experimental technique for determining the phase composition and structure of crystalline materials. However, interpretin

Hardware

KVCMAS: Efficient KV cache Correction for Shared Context in Multi-Agent Systems

arXiv:2609.34060v1 Announce Type: new Abstract: Prompt-specialized multi-agent systems enable multiple agents to share a model while performing complementary roles to solve complex tasks. However, age

hardwarearxiv-cs-lg

Large Language Models for Automated Cross-Domain Machine Learning Task Type Identification: A Benchmark Dataset and Evaluation

arXiv:2609.35335v1 Announce Type: new Abstract: Machine learning task type identification is essential for constructing valid ML pipelines, yet in practice it is typically specified manually. We inves

Learn Here, Move Less Elsewhere: Input-Conditioned Plasticity from Retained-Domain Activation Atlases

arXiv:2609.34478v1 Announce Type: new Abstract: Task-specific fine-tuning can rewrite a language model's answers beyond the training task, complicating updates that must preserve existing behavior. We

local-aiarxiv-cs-lg

Learning Geometrically-Grounded Amodal 3D Representations for View-Generalizable Robotic Manipulation

arXiv:2601.22988v2 Announce Type: replace Abstract: Real-world robotic manipulation requires visuomotor policies capable of robust 3D scene reasoning under varying camera viewpoints. While recent 3D-a

safetyarxiv-cs-ro