Search: “models”

Differentially Private Model-X Knockoffs via Johnson-Lindenstrauss Transform

arXiv:2508.04800v2 Announce Type: replace-cross Abstract: We introduce a novel privatization framework for high-dimensional controlled variable selection. Our framework enables rigorous False Discover

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Model Releases

DUA-D2C: Dynamic Uncertainty Aware Method for Overfitting Remediation in Deep Learning

DGX agent

arXiv:2411.15876v3 Announce Type: replace-cross Abstract: Overfitting remains a significant challenge in deep learning, often arising from data outliers, noise, and limited training data. To address t

model-releasesarxiv-cs-cv

9 Sept 2026

Flow3D-OPD: Multi-Teacher On-Policy Distillation for 3D Geometry Generation with Flow-Matching Diffusion Transformer

arXiv:2609.07137v1 Announce Type: new Abstract: Recent image-to-3D generation models built on flow-matching diffusion Transformers (DiT) can produce high-fidelity meshes, yet their post-training strat

safetyarxiv-cs-cv

Fusing Sequence Motifs and Pan-Genomic Features: Antimicrobial Resistance Prediction using an Explainable Lightweight 1D CNN-XGBoost Ensemble

arXiv:2509.23552v2 Announce Type: replace Abstract: Antimicrobial Resistance (AMR) is a rapidly escalating global health crisis. While genomic sequencing enables rapid prediction of resistance phenoty

GeoContext: One Context Ladder, Two Failure Modes in Vision-Language Geolocation: Flat Reliance on User-Provided Location Context and False Confirmation of Location Claims

arXiv:2609.05761v1 Announce Type: new Abstract: Visual geolocation benchmarks typically ask a model where an image was captured without accounting for the location context that users often provide. We

Applications

KODAMA: Multimodal Digital Twin Reconstruction for Urban RF Propagation Modelling

arXiv:2609.07298v1 Announce Type: new Abstract: 3D reconstruction typically strives for geometric fidelity or visual plausibility. Radio frequency digital twins (RFDT) are instead judged by whether co

applicationsarxiv-cs-cv

KTO: Model Alignment as Prospect Theoretic Optimization

arXiv:2402.01306v5 Announce Type: replace Abstract: Kahneman & Tversky's extit{prospect theory} tells us that humans perceive random variables in a biased but well-defined manner (1992); for example,

safetyarxiv-cs-lg

Matryoshka Hash Representations for Model-Aware Compact Semantic Retrieval

arXiv:2609.07276v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) depends on dense retrieval: each document is stored as a learned vector, and a query is answered by finding its n

Resolving sources of uncertainty in AI weather forecasting

arXiv:2511.14218v2 Announce Type: replace Abstract: Weather forecast uncertainty arises from imperfect analyses and forecast models, but ensemble spread alone does not reveal how distinct sources rela

Rethinking the Evaluation of Efficiency Methods for Multi-Agent Systems

arXiv:2609.05933v1 Announce Type: new Abstract: Efficiency is increasingly important for Large Language Model (LLM)-based multi-agent systems (MAS), as larger models and more agents introduce substant

Toward Sustainable Distributed LLM Inference: A Systems Synthesis and Research Agenda for an Energy-, Carbon-, and Cache-Aware llm-d Control Plane

arXiv:2609.05565v1 Announce Type: cross Abstract: Large language model (LLM) sustainability is increasingly a serving-systems problem, not only a training problem. In production, energy and carbon imp

TransNormal-2: Geometry-Grounded Rectified Flow with Edge-Aware Decoding for Precise Normal Estimation

arXiv:2609.06665v1 Announce Type: new Abstract: Diffusion-based models enable monocular geometry estimation, yet their pixel-space precision is limited by a shared, under-studied error source: VAE rec

A Generalizable Feature Extractor for Alzheimer's-Related Brain MRI Tasks

arXiv:2609.05400v1 Announce Type: new Abstract: When there is not enough labeled data to properly train deep learning models, transfer learning can help. We still do not fully understand how effective

A Schema Bounded Language Model for Refining Robot Policies Without Destabilizing Local Learning

arXiv:2609.05133v1 Announce Type: cross Abstract: This paper addresses navigation by composite heterogeneous robots in a decentralized system when policy reasoning and local control operate at differe

local-aiarxiv-cs-ai

Ask Before You Optimize: Dynamic Pre-Formulation Clarification for Interactive Optimization

arXiv:2609.05258v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to formulate optimization models from natural-language problem descriptions, yet realistic operatio

Choosing the Right Language Mode at Inference Time for Multilingual Reliability

model-releasesarxiv-cs-cl

arXiv:2609.04653v1 Announce Type: new Abstract: Multilingual large language models often struggle to reason in low- to mid-resource languages. Prior work has shown that translation can improve multili

Design Docs Are All You Need: An AI-native Machine-Learning Performance Tool

arXiv:2609.05364v1 Announce Type: cross Abstract: Machine-learning performance modeling is a uniquely hostile terrain for long-lived software: the assumptions baked into today's abstractions are inval

KVMem: Virtualizing Million-Token Agent Workspaces on a Consumer GPU

arXiv:2609.04852v1 Announce Type: new Abstract: Modern LLM agents operate in persistent workspaces whose accumulated history can exceed both GPU KV capacity and the model's native context window. Exis

Mitra-v2 Technical Report

arXiv:2609.04540v1 Announce Type: new Abstract: We introduce Mitra-v2, a tabular foundation model that delivers state-of-the-art performance on real-world classification and regression problems, from

ResLearn-XR: Residual Learning for Network Traffic and Quality-of-Experience-Aware Modeling in Extended Reality

arXiv:2609.04493v1 Announce Type: new Abstract: We present ResLearn-XR, a residual learning framework for predicting eXtended Reality (XR) network traffic and estimating Quality-of-Experience (QoE) ri

researcharxiv-cs-ai

UniMate: One Unified Model to Animate Diverse Skeletons

arXiv:2609.05415v1 Announce Type: new Abstract: Recent advances in automatic rigging now deliver animation-ready 3D assets at scale, yet generating the motion to drive them remains a bottleneck. Exist

safetyarxiv-cs-cv

FailBench: How Reliable are VLMs at Judging Robot Task Success?

arXiv:2609.03611v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly used to evaluate robot manipulation outcomes, but existing benchmarks offer limited evidence of cross-d

Agents

FiMI Banking: A Sovereign Model for Indian Retail Banking

arXiv:2609.03960v1 Announce Type: new Abstract: Banks need conversational systems that can answer product questions, assist customers with account-related requests, and operate safely within strict op

agentsarxiv-cs-ai

Improving Clinical Target Volume Segmentation Accuracy using Anatomical Priors and Active Learning for the AGITG TOPGEAR Clinical Trial

arXiv:2609.03186v1 Announce Type: cross Abstract: Training deep learning-based medical image segmentation models is challenging with limited curated datasets. For AGITG TOPGEAR, a gastric cancer trial

Physics-Informed Neural Network Surrogate for Oxygen Vacancy Dynamics in epitaxial SrTiO_3 on Si memristors via Dynamic Spectral Optimization

arXiv:2609.02966v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) offer a promising framework for modeling semiconductor devices, yet standard architectures struggle with seve

Temperature Scaling Attack Disrupting Model Confidence in Federated Learning

arXiv:2602.06638v3 Announce Type: replace-cross Abstract: Predictive confidence serves as a foundational control signal in mission-critical systems, directly governing risk-aware logic such as escalat

local-aiarxiv-cs-ai

Tensor-based Brain Surface Modeling and Analysis

arXiv:2609.03302v1 Announce Type: new Abstract: We present a unified computational approach to tensor-based morphometry in detecting the brain surface shape differences between two clinical groups bas

Agents

Unlocking Lossless Speedups in LLMs via Discrete Diffusion

arXiv:2609.04010v1 Announce Type: new Abstract: Large Language Models (LLMs) owe much of their success to next-token prediction (NTP), but their autoregressive (AR) structure requires slow, sequential

agentsarxiv-cs-lg

Beauty is in the AI of the beholder: MLLMs systematically overrate facial attractiveness

arXiv:2609.02512v1 Announce Type: new Abstract: Beauty assessments from Multimodal Large Language Models (MLLMs) are increasingly popular amongst users, companies, and aestheticians. This raises the q

CAHR-Net: Condition-Adaptive Hysteresis Reconstruction for Compact and Interpretable Magnetic Core Loss Modeling

arXiv:2609.01991v1 Announce Type: new Abstract: Magnetic core loss originates in the hysteresis loop: the energy dissipated per excitation cycle equals the loop area, and frequency, temperature, and w

IFW-BLS: Dual-Robust Broad Learning System with Intuitionistic Fuzzy Wave Loss

arXiv:2609.02422v1 Announce Type: new Abstract: Broad Learning System is an efficient randomized learning model that expands network width through feature and enhancement nodes and estimates the outpu

Pailitao-MMSearch: Building Native E-Commerce Multimodal Search Foundation

arXiv:2607.17499v2 Announce Type: replace Abstract: The evolution of e-commerce has fundamentally transformed how users search for products, shifting from simple text-based keyword queries to complex

A Compositional Kernel Model for Feature Learning

arXiv:2509.14158v3 Announce Type: replace Abstract: We study a compositional variant of kernel ridge regression in which the predictor is applied to a coordinate-wise reweighting of the inputs. Formul

A Glance Is All You Need: Single-Pass Fine-Grained Image Captioning with SimLoss

arXiv:2609.00591v1 Announce Type: new Abstract: An image may be worth a thousand words, but most captioning models describe it in only a few. Modern vision-language models produce fluent high-level ca

local-aiarxiv-cs-cv

Accelerating Chemical Kinetics for Exoplanet Atmospheres using Neural Networks

arXiv:2609.00428v1 Announce Type: cross Abstract: Observations increasingly reveal the coupled radiative, chemical, and dynamical processes that shape exoplanet atmospheres. Interpreting these atmosph

Calibration is the Bottleneck: An Action-Class Diagnostic of Multi-Turn Tool-Calling

arXiv:2609.00949v1 Announce Type: cross Abstract: Multi-turn tool calling is a core evaluation scenario for large language model (LLM) agents. On public tool-calling benchmarks, open-weight models now

local-aiarxiv-cs-ai

Conditional Flow Matching for Cross-Field MRI Harmonisation

arXiv:2609.00960v1 Announce Type: new Abstract: Magnetic resonance images of the same subject look markedly different across field strengths, which complicates the comparison and pooling of data acros

Distributed Implicit Harm: A Compositional Safety Blind Spot in MLLM-Based Video Moderation

arXiv:2609.00206v1 Announce Type: cross Abstract: Despite their growing use in video moderation, multimodal large language models (MLLMs) exhibit a compositional safety blind spot: videos composed of

safetyarxiv-cs-ai

Elite-Weighted Supervised Fine-tuning for Goal-Directed Molecular Optimization

arXiv:2609.00189v1 Announce Type: new Abstract: Goal-directed optimization is essential for steering molecular generators to propose candidates with desired properties. However, it is often implemente

EvoGS: Modeling Deformation Evolution for Dynamic Gaussian Splatting

arXiv:2609.00994v1 Announce Type: new Abstract: Recent extensions of 3D Gaussian Splatting (3DGS) enable real-time novel view synthesis in dynamic scenes by learning time-conditioned Gaussian deformat

Facet-0: A Robotic Foundation Model for Contact-Rich Precise Manipulation

arXiv:2609.01596v1 Announce Type: cross Abstract: Real-world robotic assembly at sub-millimeter tolerances demands spatial precision, compliant interaction, and robustness to contact failures. We pres

safetyarxiv-cs-lg

HBQ: Hierarchical Scaling Block Quantization with Hardware-Efficiency-Aware Design for Accurate LLM Inference

arXiv:2609.00450v1 Announce Type: cross Abstract: Block Quantization (BQ) is a promising approach for efficient deployment of large language models (LLMs), enabling low-precision computation with cont

Learning Task-Specific Antibody Representations via Function-Aware Masking

arXiv:2609.00518v1 Announce Type: new Abstract: Antibody-specific language models pretrained via masked language modeling (MLM) learn representations that are critical for downstream sequence design a

LLMPEDIA: Browsing, Verifying, and Comparing the Parametric Encyclopedic Knowledge of LLMs

model-releasesarxiv-cs-cl

arXiv:2609.01182v1 Announce Type: new Abstract: Flagship language models appear saturated on benchmarks like MMLU (Hendrycks et al., 2021), scoring above 90% - yet benchmarks test only what the experi

Potential-Guided Particle Steering for Negation-Constrained Dexterous Grasping

arXiv:2609.00555v1 Announce Type: cross Abstract: Language-driven dexterous grasp models, such as DextER, perform well when instructions specify where to grasp, but we find they fail systematically wh

Agents

RingMoClaw: An Experience-Inspired Multi-Agent Framework for Self-Evolving Research in Remote Sensing

arXiv:2609.00814v1 Announce Type: new Abstract: Remote sensing visual models have continuously advanced various interpretation tasks. However, the research process behind model improvement still heavi

agentsarxiv-cs-cv

Rock, Paper, Scissors, ... Dynamite - A Model of Disruption from New Technologies

arXiv:2609.00207v1 Announce Type: cross Abstract: We seek to understand the effect of adding disruptive highly-capable new technologies to competitions by assessing the addition of Dynamite to Rock-Pa

researcharxiv-cs-ai

TopoAlign: A Framework for Aligning Code to Math via Topological Decomposition

arXiv:2510.11944v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) excel at both informal and formal (e.g. Lean 4) mathematical reasoning but still struggle with autoformalisation,