Search: “inference”

Information-Theoretic Causal Modelling of Semiconductor Process Dynamics

arXiv:2608.14678v1 Announce Type: cross Abstract: With the progress of the semiconductor industry toward increasingly complex compute devices and tighter process tolerances, advanced process control h

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Localized TabICLv2: Scaling Tabular In-Context Learning through k-NN

DGX agent

arXiv:2608.16429v1 Announce Type: new Abstract: Foundational models for tabular data have made significant progress in recent years, with TabICLv2 reporting state-of-the-art performance on several tab

local-aiarxiv-cs-lg

18 Aug 2026

MM-BEV: Enhancing Timeliness by Computing Where and When it Matters

arXiv:2608.15437v1 Announce Type: cross Abstract: Multimodal bird's-eye-view (BEV) perception combines LiDAR depth accuracy with dense camera semantics, but its high computational cost and imperfect s

Not All History Helps: Velocity-Aware Selective Memory for Long-Horizon End-to-End Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2608.15573v1 Announce Type: new Abstract: Reliable long-horizon planning remains a key challenge in end-to-end autonomous driving. By accounting for future motion evolution and potential consequ

Not All Neighbors Matter: Understanding the Impact of Graph Sparsification on GNN Pipelines

arXiv:2603.06952v2 Announce Type: replace Abstract: As graphs scale to billions of nodes and edges, graph Machine Learning workloads are constrained by the cost of multi-hop traversals over exponentia

researcharxiv-cs-lg

OGX: An Open-Source, Vendor-Neutral Generative AI Application Server

arXiv:2608.14580v1 Announce Type: new Abstract: OGX (Open GenAI Stack) is an open-source AI application server and Python library that implements the APIs of major frontier labs (OpenAI, Anthropic, Go

PACE: Phase-Progress-Aware Credit for Long-Horizon Embodied Manipulation

arXiv:2608.15026v1 Announce Type: new Abstract: Post-training of vision-language-action (VLA) models typically relies on expert demonstrations and policy interaction trajectories. However, in long-hor

local-aiarxiv-cs-ro

PixRestore: Unified Image Restoration via Pixel Diffusion Transformer

model-releasesarxiv-cs-cv

arXiv:2608.16793v1 Announce Type: new Abstract: Unified image restoration (UIR) aims to recover high-quality (HQ) content from low-quality (LQ) images with different degradations using a single model.

Privacy-Preserving Decentralized Federated Learning via Explainable Adaptive Differential Privacy

arXiv:2509.10691v3 Announce Type: replace-cross Abstract: Decentralized federated learning enables collaborative model training without a central server, but shared model updates can still leak sensit

Prototype-Rectified Iterative Self-supervised Manifold Denoising under Severe Acoustic Shift

arXiv:2608.15037v1 Announce Type: cross Abstract: Audio-Text Foundation Models (ATMs) fail catastrophically under severe acoustic noise, yet existing adaptation strategies either rely on gradient-base

safetyarxiv-cs-lg

Risk-Adaptive Edge--Cloud Visual Reasoning for Communication-Efficient Autonomous Driving

arXiv:2608.14991v1 Announce Type: new Abstract: Cloud-hosted vision-language models (VLMs) offer greater contextual reasoning capabilities than smaller onboard models, but frequent visual uploads incr

local-aiarxiv-cs-cv

Seeing Before Answering: Training-Free Visual Layer Profiling for Vision-Language Models

arXiv:2608.16263v1 Announce Type: new Abstract: LLaVA-style Vision-Language Models (VLMs) pass visual tokens from a fixed late layer of the vision backbone, typically the penultimate one, to the langu

STAIR: Semantic-Temporal Automaton for Interpretable Reasoning in Temporal Question Answering

arXiv:2608.16224v1 Announce Type: cross Abstract: By leveraging large-scale pretraining, LLMs can interpret diverse temporal expressions and question formulations without task-specific training. Howev

TEA: Text Encoder Alignment for Robust Concept Erasure in Text-to-Image Models

arXiv:2608.15341v1 Announce Type: new Abstract: Text-to-image diffusion models can be misused to generate harmful content through adversarial or paraphrased prompts that bypass built-in safety mechani

The Unwritten Benchmark: A New Challenge for Multimodal Machine Learning in Abstract Perceptual Reasoning

arXiv:2608.14558v1 Announce Type: new Abstract: Current multimodal models have demonstrated remarkable proficiency in recognizing static visual and auditory content. However, their capacity for abstra

Hardware

TinyDETR-Pose: Towards End-to-End Real-Time Single-Stage 6DoF Object Pose Estimation with Lightweight Transformers

arXiv:2608.15297v1 Announce Type: new Abstract: Real-time 6DoF object pose estimation on resource-constrained hardware remains challenging, as accurate correspondence-based and refinement pipelines ty

hardwarearxiv-cs-cv

A Year in LLM Serving: Workload Evolution, Caching and Load-Balancing

arXiv:2608.13573v1 Announce Type: new Abstract: Large Language Model (LLM) serving has become a critical cloud workload, and realistic traces are essential for motivating and benchmarking serving syst

Content Depth Matters in Short-Video Recommendation: Rethinking the Attention Economy

arXiv:2608.13990v1 Announce Type: new Abstract: Driven by the attention economy, short-video Recommender Systems (RSs) are primarily optimized to maximize user engagement by promoting videos that capt

How Much Do Legal RAG Systems Still Hallucinate?

arXiv:2608.14210v1 Announce Type: cross Abstract: Hallucination is a major challenge for retrieval-augmented generation (RAG) systems in the legal domain, where ungrounded answers can lead to serious

Learning Unsteady Aneurysm Hemodynamics with Physics-Informed DeepONets

arXiv:2608.13629v1 Announce Type: cross Abstract: Clinically actionable, patient-specific hemodynamic assessment, specifically wall shear stress, vortex structure and pressure distributions, is critic

researcharxiv-cs-lg

Model-agnostic Retrieval-Augmented Extended Forecasting for time series

model-releasesarxiv-cs-lg

arXiv:2608.14054v1 Announce Type: new Abstract: Time series forecasting with pretrained foundation models has demonstrated strong zero-shot capabilities. However, achieving optimal performance on time

Multi-Objective Bayesian Optimization for Model Merging

arXiv:2608.14264v1 Announce Type: cross Abstract: Model merging combines trained models directly in weight space, offering a compute-efficient alternative to additional fine-tuning. Selecting merge pa

OCOO-T : A Simple and Scalable Virtual Cell Model for Transcriptional Perturbation Response Prediction

arXiv:2606.12838v2 Announce Type: replace-cross Abstract: Predicting single-cell transcriptional responses to genetic, chemical and cytokine perturbations is a fundamental challenge in computational b

Overcoming Shortcut Learning in Graph Neural Networks through Active Explanation Guidance

arXiv:2608.14121v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) can solve prediction tasks by unintentionally exploiting shortcuts---that is, edges, nodes, and features that correlate w

Owner3D: Ownership-Guided Style Writing for Training-Free Localized 3D Stylization

model-releasesarxiv-cs-cv

arXiv:2608.14078v1 Announce Type: new Abstract: Localized 3D stylization aims to modify the appearance of a specified object part while preserving the remaining surfaces. In large reconstruction model

Post-training Quantization for Hybrid Iterative Generative Models

arXiv:2608.13932v1 Announce Type: new Abstract: Iterative Generative Models (IGMs) span autoregressive and diffusion paradigms, and hybrid variants that couple them can achieve remarkable image-genera

researcharxiv-cs-lg

Program-space Diffusion for Morphology-to-Transcriptomics Prediction

arXiv:2608.14330v1 Announce Type: new Abstract: Spatial transcriptomics (ST) enables genome-wide gene expression profiling while preserving tissue architecture, but its cost and limited scalability re

Reflex: Enabling Fast and Predictive Vision-Language-Action Models for Reaction-Critical Manipulation

arXiv:2608.14379v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently achieved promising performance in robotic manipulation. However, existing benchmarks mainly evaluate

Secret-Stego Dissimilarity as a Design Axis: Invertible Coverless Image Steganography with Diffusion Models

arXiv:2608.13597v1 Announce Type: cross Abstract: Coverless image steganography (CIS) synthesizes a stego image rather than modifying an existing cover image, enabling authorized recipients to reconst

The Linear Geometry of Interpretable Tokens: Jailbreaking Attacks and Defenses for Unlearned Diffusion Models

arXiv:2504.21307v3 Announce Type: replace Abstract: Diffusion models excel at generating high-quality images but can memorize and reproduce harmful concepts when prompted. Although fine-tuning methods

Voxel-based 3D Facies Segmentation from Seismic Data: A Comparative Study

arXiv:2608.14058v1 Announce Type: cross Abstract: Seismic facies segmentation has emerged as a significant challenge in geophysics, requiring robust methods and systems to effectively identify geologi

When Denoising Hurts: Rethinking the Terminal Step of Diffusion Time Series Forecasters -- Extended Version

arXiv:2608.14067v1 Announce Type: new Abstract: Diffusion models offer a natural way to model uncertainty in time series forecasting, yet their iterative sampling process is often treated as a uniform

applicationsarxiv-cs-lg

Adjustable Text-Guided Backdoor Attacks with Natural-Word Triggers on Multimodal Pretrained Models

arXiv:2604.05809v2 Announce Type: replace-cross Abstract: This paper presents Text-Guided Backdoor (TGB), an adjustable backdoor attack against multimodal pretrained models that uses natural-word trig

applicationsarxiv-cs-lg

Beyond Correctness: Benchmarking and Aligning Response Behaviors in Hybrid-Thinking MLLMs

model-releasesarxiv-cs-cv

arXiv:2608.12781v1 Announce Type: new Abstract: Hybrid-thinking multimodal large language models (MLLMs) allow a single model to alternate between deliberative thinking and latency-efficient non-think

Agents

BrainWAM: Action-Space Coordination of Semantic Priors and Predictive Dynamics for Autonomous Driving

arXiv:2608.12854v1 Announce Type: cross Abstract: Autonomous driving requires planning under both semantic constraints and predictive dynamics. Existing end-to-end driving approaches, however, typical

agentsarxiv-cs-ai

CABS+: Efficient and Scalable Model Merging via Conflict-Aware Sparsification and Adaptive Weight Allocation

arXiv:2608.12842v1 Announce Type: new Abstract: Model merging has recently attracted significant attention as a promising paradigm for constructing unified multi-task models without requiring addition

Hardware

Enhancing Virtual Agents through SLMs and Edge-Computing: An Exploratory Evaluation of Think and Memory Processes

arXiv:2608.13420v1 Announce Type: new Abstract: Embodied intelligent virtual agents are expected to operate as persistent, adaptive, and context-aware entities within complex virtual and Metaverse wor

hardwarearxiv-cs-ai

Error-Aware Reverse Auction Mechanism for Large Language Model Routing

arXiv:2608.12719v1 Announce Type: cross Abstract: Routing each query to a cost-effective large language model (LLM) is critical for balancing quality and cost, yet most routers rely on a centralized t

Foundations of MT-PDCL: Measure-Theoretic Probabilistic Definite Clause Logic

arXiv:2608.13018v1 Announce Type: new Abstract: Standard probabilistic logic programming frameworks typically rely on grounding logic programs into discrete propositional representations. This operati

Tutorials

Generalizable Operating Room Expert with Multimodal Enhancement

arXiv:2508.08199v2 Announce Type: replace Abstract: Precise spatial modeling in the operating room (OR) is essential for intraoperative awareness, hazard avoidance, and surgical decision-making. Altho

tutorialsarxiv-cs-cv

Geometric and Behavioral Stratification in Transformer Residual Streams

arXiv:2608.12447v1 Announce Type: cross Abstract: Trained transformer models develop privileged bases: coordinate axes whose statistics differ from the rest of the residual stream. But what kind of di

researcharxiv-cs-cl

HIMEC: Directional Change Representation and Fixed-Interface Decoding for Remote Sensing Image Change Captioning

arXiv:2608.12502v1 Announce Type: new Abstract: Remote sensing image change captioning (RSICC) converts bitemporal imagery into a sentence describing semantic changes. Most RSICC methods condition cap

local-aiarxiv-cs-cv

HybridSB-MoE: Dual-Domain Schrodinger Bridges with Scene-Adaptive Expert Routing for Speech Enhancement

arXiv:2608.12715v1 Announce Type: cross Abstract: Generative speech enhancement faces three gaps: spectral models capture harmonic structure but often disrupt phase, waveform models preserve phase but

safetyarxiv-cs-ai

Identification of Probabilities of Causation: from Recursive to Closed-Form Bounds

arXiv:2505.15274v4 Announce Type: replace Abstract: Probabilities of causation (PoCs) are fundamental quantities for counterfactual analysis and personalized decision making. However, existing analyti

Interpretable Causal Discovery via Causal-Effect Constraints

arXiv:2608.12640v1 Announce Type: cross Abstract: Causal discovery aims to uncover the underlying causal relationships given data generated from a system. The goal, however, is not merely to predict c

Large Language Models Persuade Without Planning Theory of Mind

arXiv:2602.17045v2 Announce Type: replace Abstract: A growing body of work attempts to evaluate the theory of mind (ToM) abilities of humans and large language models (LLMs) using static, non-interact

safetyarxiv-cs-cl

Pandora: Leveraging Code-driven Knowledge Transfer for Unified Structured Knowledge Reasoning

arXiv:2508.17905v2 Announce Type: replace Abstract: Unified Structured Knowledge Reasoning (USKR) aims to answer natural language questions by using structured sources such as tables, databases, and k

researcharxiv-cs-cl

ProME: Prototype-Margin Environments with Repair-Aware Selection for Group-Robust Learning

arXiv:2608.13190v1 Announce Type: cross Abstract: Group-robust learning is crucial for maintaining accuracy on rare subpopulations when training-group labels are unavailable. However, existing methods