Search: “inference”

From Few-Shot Segmentation to Clinician-in-the-Loop Medical Image Analysis

arXiv:2609.10001v1 Announce Type: new Abstract: Few-shot medical image segmentation (FSMIS) seeks to delineate unseen structures from a small support set, but its standard formulation fixes task-defin

safetyarxiv-cs-cv

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How (Mis)calibrated is your Federated CLIP and what to do about it?

DGX agent

arXiv:2512.04305v3 Announce Type: replace Abstract: Vision-language models (VLMs) such as CLIP are increasingly adapted across decentralized data silos, yet the reliability of their predictions under

researcharxiv-cs-cv

10 Sept 2026

In-Place Instruction Following in Diffusion Language Models

arXiv:2609.07160v1 Announce Type: cross Abstract: Diffusion Large Language Models (dLLMs) generate text via bidirectional iterative denoising, naturally supporting user-specified constraints anchored

InstantMimic: A High Performance System for Learning Physics-based Skills in Seconds

arXiv:2609.09821v1 Announce Type: cross Abstract: Physics-based character control is a long-standing challenge in computer graphics and robotics, requiring policies that satisfy complex dynamics while

safetyarxiv-cs-ro

Interpreting Object-Dependent Concept Brittleness in Text-to-Image Diffusion Models

arXiv:2609.09909v1 Announce Type: new Abstract: Although text-to-image diffusion models generally exhibit strong prompt-following ability, we identify a persistent and previously underexplored failure

researcharxiv-cs-cv

Kernel-Managed Shared Memory for System-Wide Personalization

model-releasesarxiv-cs-lg

arXiv:2609.10144v1 Announce Type: cross Abstract: AI systems become more useful when they can adapt to the people using them, but in multi-agent systems, useful context learned by one agent often rema

Knowing Your Uncertainty -- On the application of LLM in social sciences

arXiv:2512.05461v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly being integrated into computational social science research, yet their blackboxed training and design

Lensless Gaze Is Not Private by Default: Auditing Identity Leakage Across Disclosure Surfaces

model-releasesarxiv-cs-cv

arXiv:2609.09188v1 Announce Type: new Abstract: Lensless near-eye sensing is often described as privacy-friendly because its coded measurements are visually unintelligible. Yet visual unintelligibilit

Less Is Personal: Learning Minimal Sufficient User Profiles for Personalized Language Models

arXiv:2609.08180v1 Announce Type: new Abstract: Retrieval-augmented personalization enables large language models to produce more accurate and preference-aligned outputs using relevant records retriev

Manifold-Aligned Generative Transport

arXiv:2602.19600v2 Announce Type: replace-cross Abstract: Many high-dimensional datasets concentrate near a low-dimensional structure embedded in the ambient space. Generative models for such data mus

safetyarxiv-cs-lg

Mathematical Programming in Machine Learning and Artificial Intelligence: A Unified Taxonomy of Models and Applications

arXiv:2609.07254v1 Announce Type: cross Abstract: Mathematical programming provides a common language for many decisions embedded in modern machine-learning (ML) and artificial-intelligence (AI) syste

MedDeID enables locally governed clinical-text de-identification from real or synthetic training data

model-releasesarxiv-cs-cl

arXiv:2609.10049v1 Announce Type: new Abstract: Clinical notes contain personally identifiable information (PII), restricting reuse for research and medical AI, especially when data cannot leave an in

Agents

MemForest: Efficient Agent Memory Management via EventTree Partitioning and Progressive Merging

arXiv:2609.08273v1 Announce Type: new Abstract: Agent memory systems have demonstrated significant potential in long-term dialogue, personalized assistants, and video understanding. However, continuou

agentsarxiv-cs-ai

Mode Coverage in Normalizing Flow Boltzmann Generators via Log-Ratio Variation

arXiv:2609.09473v1 Announce Type: cross Abstract: Normalizing flow Boltzmann generators retain a tractable pushforward density, but training with forward KL depends on target samples that may be biase

MOSAIC: A Universal Agent-Level Interface for Cross-Paradigm Agent Mixing and Human-AI Collaboration

model-releasesarxiv-cs-lg

arXiv:2603.01260v2 Announce Type: replace Abstract: Existing infrastructure cannot deploy agents from different decision-making paradigms within the same environment, making fair cross-paradigm compar

Multi-dimensional Preference Alignment by Conditioning Reward Itself

arXiv:2512.10237v2 Announce Type: replace Abstract: Reinforcement Learning from Human Feedback has emerged as a standard for aligning diffusion models. However, we identify a fundamental limitation in

safetyarxiv-cs-cv

Local Ai

OmniMed-FL: A Robust Multimodal Federated Learning Framework for Clinical Diagnosis

arXiv:2609.10364v1 Announce Type: new Abstract: Simultaneous assessment of medical imaging and patient records is often required in clinical diagnosis. However, standard machine learning algorithms ca

local-aiarxiv-cs-lg

On-Policy Distillation for Vision-Language Model Adaptation, an Effective Paradigm on Low-Quality Multimodal Data

arXiv:2609.10321v1 Announce Type: new Abstract: Knowledge distillation offers an efficient route to transfer a task-adapted vision-language teacher to a compact student. The training target in current

safetyarxiv-cs-cl

Personalized Execution Time Optimization for Billion-Scale Scheduled Jobs

arXiv:2203.06158v3 Announce Type: replace Abstract: Scheduled batch jobs are widely used on asynchronous computing platforms to execute enterprise applications such as promotional notifications and ca

safetyarxiv-cs-lg

PiMRef: Deducing Ever-evolving Spear-phishing Emails with Knowledge Base Invariants

arXiv:2507.15393v2 Announce Type: replace-cross Abstract: Phishing email is a critical step in the cybercrime kill chain due to the high reachability of victims' email accounts and the low cost of lau

ProbPlug: A Plugin Uncertainty Network for Reliable Confidence in LLM Binary Classification

arXiv:2609.10122v1 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance across a broad range of classification settings, yet the reliability of their predictions

researcharxiv-cs-cl

Reasoning-Aware Compression: Identifying and Protecting Vulnerable Reasoning Circuits for Energy-Efficient LLM Deployment

arXiv:2609.05512v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) impose substantial energy costs during deployment, yet current compression methods apply uniform quantization across all c

RedKnot-MLA: Multi-Head Offline-Online Reuse for DeepSeek-V4 Long-Context Serving

arXiv:2609.07008v1 Announce Type: new Abstract: Multi-head latent attention (MLA) exposes many logical query heads through one packed latent KV stream. This representation is memory efficient, but it

Router Prior Bias: Preserving Base Routing Structure in MoE Post-Training

arXiv:2609.08115v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) pretraining relies on an auxiliary load-balancing loss (LBL) to drive per-expert utilization toward uniformity. Post-training i

SalamandraTA at WMT 2026 Terminology Shared Task: Hard Examples Are Better Teachers

model-releasesarxiv-cs-cl

arXiv:2609.09999v1 Announce Type: new Abstract: Terminology-aware translation asks for more than a correct translation: the output must use the exact terms a glossary prescribes. The standard recipe,

Same Values, Different Languages? From Multilingual Probing to Steering LLMs Toward Chinese Social Values

arXiv:2609.08515v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly integrated into human society, aligning them with pluralistic social values has become a critical pri

safetyarxiv-cs-ai

Scaling E-Commerce Attribute Extraction with Parallel Decoding

arXiv:2609.09716v1 Announce Type: new Abstract: Customers rely on specific product attributes to compare products and make purchasing decisions, but e-commerce catalogs are messy and unstructured, mak

applicationsarxiv-cs-cl

SequenceO1: End-to-End Ultra-Long (100K) Sequence Modeling in Recommendation with Low-Rank Caching

arXiv:2609.08443v1 Announce Type: cross Abstract: Modeling long-term user behavior is central to sequential recommendation and billion-scale industrial recommender systems, yet production ranking mode

applicationsarxiv-cs-ai

Hardware

SkNeXt enables topology-guided neuronal reconstruction from petabyte-scale microscopy data

arXiv:2609.09832v1 Announce Type: new Abstract: Recent advances in high-resolution fluorescence and electron microscopy have enabled nanoscale imaging across increasingly large brain volumes, but the

hardwarearxiv-cs-cv

SRD-GUARD: A Defense Framework of LLMs via Semantic Rewriting and Joint Multi-Model Scoring for Latent Intent Exposure

arXiv:2609.06540v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in safety-critical applications, yet jailbreak attacks can conceal harmful intent through role-

Local Ai

Steering Diffusion Priors with Sparse Observations for High-Resolution Temperature Downscaling

arXiv:2609.09247v1 Announce Type: cross Abstract: Local heatwave hazard depends on fine-scale air temperature, but ground stations are sparse and reanalysis products such as ERA5 cannot resolve the te

local-aiarxiv-cs-lg

SynThermFace: Amplifying Limited Paired Data for Visible-Thermal Face Recognition via Synthetic Data Generation

arXiv:2609.10303v1 Announce Type: new Abstract: Face recognition (FR) is a widely used modality for biometric authentication, but conventional models rely on visible-spectrum imagery and degrade when

researcharxiv-cs-cv

Tactile Memory with Soft Robot: Robust Object Insertion via Masked Encoding and Soft Wrist

arXiv:2601.19275v2 Announce Type: replace-cross Abstract: Tactile memory, the ability to store and retrieve touch-based experience, is critical for contact-rich tasks such as key insertion under uncer

Take What You Need: Flexible Multi-Task Semantic Communications with Channel Adaptation

arXiv:2502.08221v2 Announce Type: replace Abstract: The growing demand for efficient semantic communication systems capable of managing diverse tasks and adapting to fluctuating channel conditions has

researcharxiv-cs-cv

The Surprising Effectiveness of Approximate Value Iteration in Self-Play

arXiv:2609.09094v1 Announce Type: new Abstract: Combining search with function approximation has driven major advances in game-playing programs, making self-play algorithms more competitive than ever.

Theoretical Analysis of Measure Consistency Regularization for Partially Observed Data

arXiv:2602.01437v2 Announce Type: replace Abstract: The problem of corrupted data, missing features, or missing modalities continues to plague the modern machine learning landscape. To address this is

applicationsarxiv-cs-lg

Through the Looking Glass: Directly Reading and Writing Transformers

arXiv:2609.10210v1 Announce Type: new Abstract: How many of a transformer's components decide a token? Counted by the absolute value of each unit's and channel's contribution to the logit, one predict

researcharxiv-cs-cl

Tutorials

Tracing Energy Flow: Learning Tactile-based Grasping Force Control to Reduce Slippage in Dynamic Object Interaction

arXiv:2512.21043v2 Announce Type: replace Abstract: Regulating grasping force to reduce slippage during dynamic object interaction remains a fundamental challenge in robotic manipulation, especially w

tutorialsarxiv-cs-ro

Train Overcomplete, Deploy Compact: Scaling Recovery Capacity for Structured LLM Pruning

arXiv:2609.06974v1 Announce Type: cross Abstract: Large language models achieve strong performance across diverse tasks, but deployment remains costly because of memory, latency, and energy demands. S

applicationsarxiv-cs-ai

'Transforming' LHCb: self-supervised maps of heavy-flavour decays

arXiv:2609.09275v1 Announce Type: cross Abstract: Decays of beauty and charm hadrons provide sensitive probes of physics beyond the standard model, including decays with invisible particles, in which

TreeThink: A Modular Tree Search Library for Mathematical Reasoning with LLMs

model-releasesarxiv-cs-cl

arXiv:2607.11258v2 Announce Type: replace Abstract: Tree search algorithms enable systematic exploration of the proof space in neural theorem proving. Existing LLM tree search libraries primarily targ

Vision-language models know more about agriculture than they show and rubric-grounded verifications close the gap

model-releasesarxiv-cs-cv

arXiv:2609.09417v1 Announce Type: new Abstract: Vision-language models (VLMs) show promise for agricultural classification, but zero-shot performance on disease, pest, damage, quality, and species ide

Agents

VLX-VR: An Agentic-Aware Video Reasoning Model

arXiv:2609.09985v1 Announce Type: new Abstract: Real-world video understanding requires integrating visual, audio, textual, and temporal evidence distributed across a video. Yet many pipelines use a f

agentsarxiv-cs-cl

WAPP: Safe Learning of Positive Security WAF Policies from Live Traffic

arXiv:2609.06840v1 Announce Type: cross Abstract: Web Application Firewalls (WAFs) mainly rely on signatures to detect known attacks, which can leave gaps against modified or previously unseen payload

safetyarxiv-cs-ai

We Built a Mirror and Mistook It for a Mind: Causal Liability and the Fallacy of AI Consciousness

arXiv:2609.06715v1 Announce Type: new Abstract: The contemporary debate over machine consciousness begins from a concealed assumption: that the object called 'AI' already constitutes the kind of entit

What Fixed-Rollout pass@k Evaluations Can Identify

arXiv:2609.09245v1 Announce Type: cross Abstract: Repeated-sampling evaluations increasingly extrapolate pass@k far beyond the number n of samples collected per problem. We show that, in the pooled/ra

What LLM Trading Agents Actually Do in Production: A Six-Month, Population-Scale Record from Two Fleets

arXiv:2609.05663v1 Announce Type: new Abstract: We present a continuous, population-scale measurement record of autonomous language-model trading agents operating in production across two systems with

What Symmetry Buys a Learned Motion Planner

model-releasesarxiv-cs-ro

arXiv:2609.10033v1 Announce Type: new Abstract: Learning-based motion planners pay at training what classical planners pay per query. Trained in world coordinates, they relearn the same motion at ever