Search: “inference”

MUSE: A Run-Centric Platform for Multimodal Unified Safety Evaluation of Large Language Models

arXiv:2603.02482v2 Announce Type: replace-cross Abstract: Safety evaluation of multimodal large language models requires tracking not only whether an attack succeeds, but also how the interaction unfo

safetyarxiv-cs-cl

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Normalized Low-Rank Adaptation

DGX agent

arXiv:2608.31036v1 Announce Type: new Abstract: While low-rank adaptation (LoRA) is widely used for parameter-efficient model adaptation, how to regularize its training dynamics for stable and effecti

model-releasesarxiv-cs-lg

1 Sept 2026

Not the Same Protector: Deployment-Dependent Protective Intervention in LLMs

arXiv:2608.29136v1 Announce Type: cross Abstract: We ask whether a model protects a user in the same way when that user speaks rather than types. Using a single distress vignette---a physical injury o

safetyarxiv-cs-ai

On the Instance Hardness as a Decision Criterion in TinyML Systems

arXiv:2608.29913v1 Announce Type: new Abstract: TinyML includes the implementation of machine learning on devices with limited memory and computing resources. With the development of technology, AI sy

On the Recoverability of Private Information Unlearning in Large Language Models

arXiv:2608.29943v1 Announce Type: cross Abstract: Large language models (LLMs) can memorize sensitive information, raising serious privacy concerns. Machine unlearning offers a potential solution to r

One Adapter, Many Tasks: Task-Conditioned Feature Transformations for Continual Learning

model-releasesarxiv-cs-cv

arXiv:2608.31096v1 Announce Type: new Abstract: Class-incremental learning (CIL) requires a model to incrementally learn tasks that contain new classes without accessing earlier training data while pr

Quantifying and Mitigating Korean Jamo-Level Typographical Vulnerabilities in Large Language Models

arXiv:2608.30229v1 Announce Type: new Abstract: Korean introduces an additional typographical perturbation level not captured by ordinary character-level edit models: because syllable blocks are inter

Local Ai

Real-Time Scene-Adaptive Tone Mapping for High-Dynamic Range Object Detection

arXiv:2608.30400v1 Announce Type: new Abstract: High-dynamic-range (HDR) images, with their rich tone and detail reproduction, hold significant potential to enhance computer vision systems, particular

local-aiarxiv-cs-cv

RealCAD: Towards Real-World Image-to-CAD Reconstruction under Domain Shift and Parameter Bias

model-releasesarxiv-cs-cv

arXiv:2608.30617v1 Announce Type: new Abstract: Reconstructing editable Computer-Aided Design (CAD) models from images is essential for downstream modification, manufacturing, and design reuse. Howeve

RENSA: Rich Environment Metadata to Navigate Shared and Distributed Endpoints for Automated Federated SPARQL Query Generation

arXiv:2608.28963v1 Announce Type: cross Abstract: The number of knowledge graph databases has increased significantly with the proliferation of knowledge graph technologies. Knowledge graphs enable th

Review Before Trust: Source-Grounded Integrity Gates for AI-Assisted Personal Health Records

arXiv:2608.29965v1 Announce Type: new Abstract: Large language models can convert medical documents into structured data, but plausible output may still be unsupported by the source. Persisting such o

safetyarxiv-cs-ai

ReViV: Reconstructing the Viewer and the View in 4D from Monocular Egocentric Video

arXiv:2607.17790v2 Announce Type: replace-cross Abstract: Egocentric devices, such as wearable front-facing cameras, provide a unique perspective for capturing the continuous interaction between a hum

Robust Broad Learning System with Wave Loss for Classification under Data Uncertainty

arXiv:2608.29983v1 Announce Type: new Abstract: Broad Learning System (BLS) offers an efficient alternative to deep architectures by enabling fast learning through randomized feature mapping and close

RouteSparse: Input-Conditional Pattern Routing for Budgeted Long-Context Prefilling

arXiv:2608.29058v1 Announce Type: new Abstract: Dynamic sparse attention can reduce the quadratic cost of long-context prefilling without changing model weights. MInference assigns each attention head

SimGuide: Typed Multi-Context User Representations for Preference-Conditioned Agent Planning

model-releasesarxiv-cs-ai

arXiv:2608.24888v2 Announce Type: replace Abstract: Agents that act on a user's behalf must plan differently for different users, and increasingly do so from some structured representation of user con

SIR: Self-improving Red-teaming for Compute Use Agents

model-releasesarxiv-cs-ai

arXiv:2608.30207v1 Announce Type: cross Abstract: Computer use agents (CUAs) are vision-language models that perceive a screen and act on a real operating system through mouse, keyboard, and terminal,

Spatial Entropy based Partitioning for Spatiotemporal Graph Unlearning

arXiv:2608.29360v1 Announce Type: new Abstract: Spatiotemporal graphs underpin applications such as traffic forecasting, weather forecasting, and healthcare monitoring. Privacy regulations such as the

applicationsarxiv-cs-lg

State of Health Estimation using Convolutional and Bidirectional LSTM Neural Networks tuned by Bayesian Optimization

arXiv:2608.30593v1 Announce Type: new Abstract: In this research, a novel framework is proposed for the SOH estimation, which employs a hybrid deep learning architecture of a concatenation of a Convol

researcharxiv-cs-lg

Local Ai

STEP: A Modular Silent Trial Engine for Operational Evaluation of Digital Pathology AI in Routine Workflow

arXiv:2608.28708v1 Announce Type: cross Abstract: Prospective silent trials provide an important bridge between retrospective validation of artificial intelligence (AI) models and their use in clinica

local-aiarxiv-cs-cv

Stream-DiffVSR: Low-Latency Streamable Video Super-Resolution via Auto-Regressive Diffusion

arXiv:2512.23709v3 Announce Type: replace Abstract: Diffusion-based video super-resolution (VSR) methods deliver strong perceptual quality but are often unsuitable for latency-sensitive scenarios due

researcharxiv-cs-cv

Stress-Testing Efficient Responsible-AI Evaluation: When Compute Savings Change Benchmark Conclusions

arXiv:2608.31108v1 Announce Type: new Abstract: Efficient evaluation changes the protocol used to support claims about model behavior, yet it is rarely tested whether those claims remain stable after

TDDM-Melatt: A Decoupled Memory and Diffusion Framework for Generalizable Encrypted Traffic Classification

arXiv:2608.30745v1 Announce Type: new Abstract: The widespread adoption of encrypted traffic poses severe challenges to current security situational awareness systems based on network traffic monitori

Toward Generalizable Deep Learning Based Peatland Fire Detection via Walsh Hadamard Transform and Domain Adaptation

arXiv:2603.02465v2 Announce Type: replace-cross Abstract: Machine learning-based wildfire detection has advanced significantly using deep learning models trained on large wildfire image and video data

Tracing the Latent Threads: A Mechanistic Study of How LLMs Represent and Operationalize Race and Ethnicity Cues

arXiv:2601.12868v2 Announce Type: replace Abstract: Large language models (LLMs) increasingly operate in high-stakes settings where demographic attributes such as race and ethnicity may be explicitly

safetyarxiv-cs-cl

Transformer-Encoder Trees for Efficient Multilingual Machine Translation and Speech Translation

model-releasesarxiv-cs-ai

arXiv:2509.17930v3 Announce Type: replace-cross Abstract: Multilingual translation suffers from computational redundancy, especially when translating into multiple languages simultaneously. In additio

A comprehensive and trustworthy benchmark of AI methods for change detection in Earth observation

model-releasesarxiv-cs-cv

arXiv:2608.28247v1 Announce Type: new Abstract: Change detection in Earth observation (EO) is critical for monitoring land surface transformations, yet recent research in the field is constrained by i

AIM: Anchor Identity Features, Then Match for Multimodal Large Language Model Unlearning

arXiv:2608.28312v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) can memorize identity-specific facts about people in their fine-tuning data, creating privacy risks when a pe

Are These Modules Worth Their Cost? A Paradigm-Level Accuracy-Cost Analysis of In-context Learning Text-to-SQL

arXiv:2608.28432v1 Announce Type: new Abstract: Recent advances in in-context learning (ICL) text-to-SQL have substantially improved execution accuracy on public benchmarks by assembling increasingly

D-TAIA: Domain-Aware LLM Adaptation for Multi-Task Predictive Process Monitoring

arXiv:2608.28236v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) enables organizations to forecast future process behavior, such as the next activity and remaining time of ongoing c

Dynamic Alignment Compensation for Hallucination Mitigation in Large Vision-Language Models

arXiv:2608.28058v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) remain prone to hallucinations, producing responses that are irrelevant or inconsistent with the multimodal input.

safetyarxiv-cs-cv

From Perspective to Fisheye Depth Estimation and Open-Vocabulary Segmentation

arXiv:2608.27860v1 Announce Type: new Abstract: Vision foundation models are capable of generalizing across 3-dimensional (3D) scenes with high-fidelity estimates; their empirical success can be attri

safetyarxiv-cs-cv

Generalized Splines and Gaussian Processes

arXiv:2608.28446v1 Announce Type: cross Abstract: For finite-dimensional linear inverse problems where the variables are Gaussian, it is well-known that the minimum-mean-square error estimator takes t

researcharxiv-cs-lg

Improved off-policy training of diffusion samplers

arXiv:2402.05098v5 Announce Type: replace Abstract: We study the problem of training diffusion models to sample from a distribution with a given unnormalized density or energy function. We benchmark s

Node-wise Feature Encoding for Neural Performance Prediction

arXiv:2608.27794v1 Announce Type: new Abstract: As neural networks are increasingly deployed on resource constrained edge devices, accurate prediction of latency and energy is critical for efficient n

Real-Time Musculoskeletal Surrogates for Pediatric Cerebral Palsy: a Credibility Pilot

arXiv:2608.28371v1 Announce Type: new Abstract: Real-time musculoskeletal (MSK) surrogates could support personalized rehabilitation for children with cerebral palsy (CP), but their credibility depend

researcharxiv-cs-cv

Roleplaying with Structure: Synthetic Therapist-Client Conversation Generation from Questionnaires

arXiv:2510.25384v2 Announce Type: replace Abstract: Large Language Models (LLMs) are promising tools for synthetic data generation in mental health. However, privacy policies and restrictions forced p

Tutorials

SCALE: Self-uncertainty Conditioned Adaptive Looking and Execution for Vision-Language-Action Models

arXiv:2602.04208v3 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for general-purpose robotic control, with test-time scaling (TTS) gai

tutorialsarxiv-cs-lg

Simplex-to-Euclidean Bijection for Conjugate and Calibrated Multiclass Gaussian Process Classification

arXiv:2603.16621v2 Announce Type: replace Abstract: We propose a conjugate and calibrated Gaussian process (GP) model for multi-class classification by exploiting the geometry of the probability simpl

applicationsarxiv-cs-lg

Hardware

SOMTab: Set-Order Mamba for Efficient Tabular In-Context Learning

arXiv:2608.27882v1 Announce Type: new Abstract: Tabular foundation models based on in-context learning have recently emerged as strong alternatives to task-specific model fitting. However, the current

hardwarearxiv-cs-lg

Local Ai

Spectral Query-Key Product Weight Steering for Training-Free VLM Hallucination Mitigation

arXiv:2606.20419v2 Announce Type: replace Abstract: Vision-language models (VLMs) often generate fluent but visually unsupported descriptions, especially by mentioning objects absent from the image. W

local-aiarxiv-cs-cv

Agents

VICT: Verifier-Instrumented Credit Tracing for Long-Horizon LLM Agent Reinforcement Learning

arXiv:2608.28128v1 Announce Type: new Abstract: Fine-grained credit assignment is a central challenge in reinforcement learning for long horizon LLM agents. Standard objectives often train from progra

agentsarxiv-cs-lg

Why Didn't It Check? Unsupported Final Claims and Their Repair in Two Tool-Equipped Language Models

arXiv:2608.27768v1 Announce Type: cross Abstract: A language model with access to tools can commit to a final claim unsupported by the evidence it has seen, even when a single available tool call woul

CLAP: Cross-Embodiment Video World Models are Zero-Shot Physical Simulators

arXiv:2608.27406v1 Announce Type: cross Abstract: State-of-the-art action-conditioned video models are typically restricted to a single robot embodiment, preventing them from leveraging the vast corpu

applicationsarxiv-cs-ai

Classical and Hybrid Quantum Machine Learning for Trigger-Like Event Selection on CMS Open Data: An Eight-Qubit, PCA-Constrained Benchmark

arXiv:2608.26224v1 Announce Type: cross Abstract: Event triggering sits at the heart of high-energy physics, where the rare events of interest must be retained while an overwhelming background is disc

Compositional Generalization via Structural Identification in a Category-Theoretic Framework

arXiv:2608.26465v1 Announce Type: new Abstract: Compositional generalization is usually evaluated through model accuracy. We instead ask which structural or lexical identifications make held-out COGS

Diagnosing Conformal Prediction Failures Under Distribution Shift: A COVID-19 Case Study

arXiv:2601.00908v2 Announce Type: replace-cross Abstract: Conformal prediction provides distribution-free coverage guarantees, but these degrade under distribution shift - and practitioners lack tools

applicationsarxiv-cs-ai

Discovering Relationships in Data Lakes Using Large Language Models: An Industrial Case

arXiv:2608.26750v1 Announce Type: new Abstract: Data lakes rely on metadata to remain usable, yet this meta data is often limited or weakly informative for column relationship discovery, especially in

Agents

Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive Reasoning

arXiv:2509.03345v3 Announce Type: replace Abstract: Non-deductive reasoning, encompassing inductive and abductive reasoning, is essential in addressing complex real-world questions. One key feature of

agentsarxiv-cs-ai