Search: “inference”

Barycentric Anchored Weight Search for Robust Model Merging

arXiv:2610.14017v1 Announce Type: cross Abstract: We propose Barycentric Anchored Search, a post-hoc weight-space procedure for improving fine-tuned vision models under distribution shift without addi

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Model Releases

BaT-SAM: Introducing Inductive Bias into SAM via a Mixture of Convolutional Experts for Brain Tumor Segmentation

DGX agent

arXiv:2610.15330v1 Announce Type: new Abstract: Accurate brain tumor segmentation from magnetic resonance imaging (MRI) is essential for diagnosis and treatment planning; however, manual delineation i

model-releasesarxiv-cs-cv

14 Oct 2026

Bayesian Nonparametric Thompson Sampling for Multi-Armed Bandits

arXiv:1808.02932v5 Announce Type: replace-cross Abstract: In stochastic multi-armed bandits, rewards are generated by an unknown distribution; the world's reward uncertainty induces the exploration-ex

Beyond a Better Score: Long-Horizon Agentic ML Development and Evaluation Protocol for Physics Time Series

arXiv:2610.14024v1 Announce Type: new Abstract: Physics time-series data are central to fundamental discoveries involving dark matter, neutrinos, and gravitational waves. Machine learning has shown st

Beyond Policy Rollouts: Embedding-Space Directional Exploration with Anchored Noise for LLM RLVR

arXiv:2610.16105v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) typically uses small rollout groups per prompt, where repeated sampling from the same policy can y

Bifocal: Training-Free Mixed Granularity Visual Token Pruning for Multimodal LLMs

arXiv:2610.18399v1 Announce Type: new Abstract: Visual token pruning for multimodal large language models (MLLMs) appears highly effective, with existing methods retaining over 95% of unpruned perform

BigCell: Generating Gigapixel Whole-Slide Images

arXiv:2610.14261v1 Announce Type: new Abstract: Whole-slide images (WSIs) are gigapixel-scale digital scans of histopathology tissue and serve as the primary basis for cancer diagnosis. Existing histo

Bottlenecked semantic compression by representation reconstruction

arXiv:2610.17412v1 Announce Type: new Abstract: Vision Transformers incur high computational costs when processing long visual token sequences. Existing reduction methods typically rank tokens indepen

Bouncy particle sampler with infinite exchanging parallel tempering

arXiv:2509.02003v2 Announce Type: replace Abstract: Markov chain Monte Carlo is one of the most useful tools for obtaining samples from complex distributions, such as posterior distributions in Bayesi

Box-WAM: Box Trajectories as Compact State Representations for World Action Models

arXiv:2610.17526v1 Announce Type: new Abstract: World action models (WAMs) are a category of policy models that ex- plicitly predict both actions and future world states. They have been shown to outpe

BridgeTwist: Twisting Schrodinger Bridges for Training-Free Conditional Sampling

arXiv:2610.18658v1 Announce Type: new Abstract: Generative models are often required to serve many downstream conditional tasks. In the training-free setting, a pretrained unconditional model is reuse

BridgeWAM: Bridging Video and Action Experts via Latent Bridge Queries

arXiv:2610.14746v1 Announce Type: cross Abstract: World Action Models (WAMs) commonly couple video and action experts through dense, layer-wise Mixture-of-Transformers (MoT) attention, exposing action

tutorialsarxiv-cs-cv

BrowseSafe++: Benchmarking Prompt Injection Detection Across Web Contexts, Languages, and Browser Views

arXiv:2610.17457v1 Announce Type: cross Abstract: Browser agents need to make decisions and execute actions on behalf of users while consuming untrusted webpages, creating opportunities for malicious

CAG-WAM: Causal Action-Gain World Action Models for Robot Manipulation

arXiv:2610.14720v1 Announce Type: new Abstract: World Action Models (WAMs) combine action generation with future prediction, allowing predicted futures to support action evaluation and robot decision

CAPTOR: a vision-language foundation model for Chest-Abdomen-Pelvis Oncologic CT

arXiv:2610.14226v1 Announce Type: new Abstract: Purpose : To develop and evaluate CAPTOR, a deep-learning vision-language foundation model for oncologic chest-abdomen-pelvis (CAP) CT interpretation. M

CartoVec: General-Purpose Location Embeddings from Open Map Data

arXiv:2610.17190v1 Announce Type: new Abstract: Geographic coordinates are common inputs in applied machine learning, but latitude and longitude describe position rather than the surrounding environme

tutorialsarxiv-cs-lg

CAST-ASD: Causal Attention over Speakers and Time for Online Active Speaker Detection

arXiv:2610.14676v1 Announce Type: new Abstract: We present CAST-ASD (Causal Attention over Speakers and Time), a causal joint model for active speaker detection (ASD). Recent ASD models improve perfor

Causal Identification from Counterfactual Data: Completeness and Bounding Results

arXiv:2602.23541v3 Announce Type: replace-cross Abstract: Previous work establishing completeness results for counterfactual identification has been circumscribed to the setting where the input data b

Characterizing the Separability Gap in Prior-Data Fitted Networks

arXiv:2610.14989v1 Announce Type: new Abstract: Prior-data fitted networks (PFNs) are transformers pretrained on simulated datasets to approximate Bayesian posterior predictive distributions. Standard

tutorialsarxiv-cs-lg

Chunk-wise Model-based Policy Optimization

arXiv:2610.14564v1 Announce Type: cross Abstract: Model-based reinforcement learning has shown superior sample efficiency by leveraging the learned latent dynamics either in the form of derivative-fre

Cite Pretrain: Retrieval-Free Knowledge Attribution for Large Language Models

arXiv:2506.17585v4 Announce Type: replace-cross Abstract: Large language models can answer questions correctly and still hallucinate their citations. Most citation systems address this by retrieving d

CLNO: Conservative Local Neural Operator for Compressible Flow Prediction

arXiv:2610.16040v1 Announce Type: cross Abstract: We propose a conservative local neural operator (CLNO) for accurate and generalizable autoregressive prediction of compressible flows. Building upon t

Co-Creative Learning via Metropolis-Hastings Interaction between Humans and AI

arXiv:2506.15468v2 Announce Type: replace-cross Abstract: We propose co-creative learning as a novel paradigm where humans and AI, i.e., biological and artificial agents, mutually integrate their part

Code2Worlds-2: Physically Plausible Agent Harness for Embodied World Simulation

arXiv:2610.17651v1 Announce Type: cross Abstract: Recent coding large language models (LLMs) can synthesize dynamic 4D worlds from natural language, but the resulting content remains a visual artifact

Collaborative Planning for UAV-UGV Teams under Operational Constraints via Masked Error-bounded Neuro-Symbolic Diffusion

arXiv:2610.18850v1 Announce Type: new Abstract: Collaborative planning under operational constraints is essential for heterogeneous robot teams in large-scale missions. Unmanned Aerial Vehicles (UAVs)

Agents

ConDenseDrive: Knowledge-Dense, Token-Sparse Visual Encoder for End-to-End Autonomous Driving

arXiv:2610.16908v1 Announce Type: new Abstract: End-to-end driving requires rich spatiotemporal representations to support scene understanding and trajectory planning under strict latency constraints.

agentsarxiv-cs-cv

Congrats to @lightseekorg on the impressive TokenSpeed results! 🚀 Great to see Qwen3.8-Flash-Next reaching 685 output tokens/s per user on …

Congrats to @lightseekorg on the impressive TokenSpeed results! 🚀 Great to see Qwen3.8-Flash-Next reaching 685 output tokens/s per user on Nvida GPUs. Excited to see the community unlock more of Qwen’

model-releasesqwen--x

Constraint-Decomposed Impedance Control from Generative Policy for Articulated Object Manipulation

arXiv:2610.16316v1 Announce Type: new Abstract: Articulated object manipulation tasks such as opening doors, tightening bolts, and pulling drawers impose kinematic constraints on a robot end-effector'

Agents

Context-aware Bayesian Fusion for Multimodal Object Detection

arXiv:2610.18741v1 Announce Type: new Abstract: Reliable detection of pedestrians and road users is essential for the safe operation of autonomous vehicles. However, this task becomes increasingly cha

agentsarxiv-cs-cv

Contrastive Metric Learning for Point Cloud Segmentation in Highly Granular Detectors

arXiv:2603.23356v2 Announce Type: replace-cross Abstract: We propose a novel clustering approach for point-cloud segmentation based on supervised contrastive metric learning (CML). Rather than predict

D-World: An Explicit World-Language-Action Model with Recursive Self-Improvement under Dual Control

model-releasesarxiv-cs-ro

arXiv:2610.17114v1 Announce Type: new Abstract: Frontier large language models (LLMs) now reason about space well enough to program robots, yet the world models behind robot policies are implicit, hel

Deep Jump Gaussian Processes for Surrogate Modeling of High-Dimensional Piecewise Continuous Functions

arXiv:2510.21974v3 Announce Type: replace Abstract: We introduce Deep Jump Gaussian Processes (DJGP), a novel method for surrogate modeling of a piecewise continuous function on a high-dimensional dom

Deep Learning-based Mechanical Characterization of Synthetically Generated Plant Fibers under Transverse Compression

arXiv:2610.16529v1 Announce Type: new Abstract: Plant fibers are increasingly used as sustainable reinforcements in composites, but the intrinsic variability of their microstructure causes substantial

tutorialsarxiv-cs-cv

Deficit-Driven Stratified Acquisition for Building STRATA-S12: An Open SAR-Optical Corpus for Self-Supervised Learning

arXiv:2610.17680v1 Announce Type: cross Abstract: Building a co-registered SAR-optical corpus for self-supervised Earth Observation is above all an acquisition problem, yet the main multi-modal datase

Local Ai

DeltaNet-PC: Test-Time Memory Without Backpropagation Through Time

arXiv:2610.15185v1 Announce Type: new Abstract: Test-time memorization of sequential information is a foundational capability for any intelligent system that needs to rapidly store and retrieve data,

local-aiarxiv-cs-lg

Dependency Reasoning for Aspect Sentiment Quadruple Prediction

arXiv:2610.14873v1 Announce Type: cross Abstract: Aspect Sentiment Quadruple Prediction (ASQP) is fundamentally a relational reasoning problem: identifying aspect-opinion-category-sentiment quadruples

Depth Memory

arXiv:2610.18809v1 Announce Type: new Abstract: Residual connections propagate information through a network by additively accumulating layer outputs. Recently proposed alternatives, such as Manifold-

DexFLEX: Contact-Aware Foundation Controller for Command-Guided Dexterity

arXiv:2610.14372v1 Announce Type: cross Abstract: Dexterous robot hands can receive useful motion intent from teleoperation or learned policies, but successful execution also depends on contact decisi

Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model

arXiv:2502.05505v4 Announce Type: replace-cross Abstract: Differentially private (DP) synthetic data enables the use of sensitive datasets while providing strong privacy guarantees. Recently, Private

Distance Marching for Generative Modeling

arXiv:2602.02928v2 Announce Type: replace Abstract: Modern generative models based on diffusion or flow matching transport noise toward the data manifold, without representing the data manifold explic

Agents

DoubtLess: Training-Free Contrastive Decoding for Efficient Reasoning

arXiv:2610.18862v1 Announce Type: cross Abstract: Reasoning models achieve strong performance through long chains of thought (CoT), but often spend more tokens than needed to solve a problem. Existing

agentsarxiv-cs-lg

Applications

DRanker: A Transformer-Based Multi-Task Ranking Model for the Disney+ Homepage

arXiv:2610.15696v1 Announce Type: new Abstract: We present DRanker (Disney+ Ranker), a transformer-based multitask ranking model serving personalized recommendations on the Disney+ homepage. We descri

applicationsarxiv-cs-lg

DreamWorld: Unified World Modeling in Video Generation

arXiv:2603.00466v2 Announce Type: replace Abstract: Despite impressive progress in video generation, existing models remain limited to surface-level plausibility, lacking a coherent and unified unders

safetyarxiv-cs-cv

Drift, Then Spread: Learning One-Step Generative Policies for Online Reinforcement Learning

arXiv:2610.15662v1 Announce Type: new Abstract: Generative policies offer expressive action distributions for online reinforcement learning (RL), but many diffusion- and flow-based policies require co

DSM-Free UAV Visual Localization via Latent-Depth Variable Projection and Structure-Adaptive Coupling

arXiv:2610.14945v1 Announce Type: new Abstract: Visual localization enables unmanned aerial vehicles (UAVs) to maintain absolute positioning in GNSS-denied environments. A common approach matches UAV

Local Ai

DT-LoRA: Reaching Beyond the Tangent Space of Low-Rank Adaptation

arXiv:2610.17730v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) often underperforms full fine-tuning. We investigate this performance gap through a tangent-space lens: factorized updates ar

local-aiarxiv-cs-cv

DVTR-KD: Distilling Vision-Language Models via Intermediate Visual Token Reconstruction

arXiv:2610.17853v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved strong performance on diverse vision-language tasks, but their computational demands limit deploy

e1: Learning Adaptive Control of Reasoning Effort

arXiv:2510.27042v3 Announce Type: replace-cross Abstract: Increasing the thinking budget of AI models can significantly improve accuracy, but not all questions warrant the same amount of reasoning. Us