Search: “evaluation”

Interpretable Depression Detection from Social Media Text Using LLM-Derived Embeddings

arXiv:2506.06616v2 Announce Type: replace Abstract: Accurate and interpretable detection of depressive language in social media can support early identification of mental health conditions and inform

researcharxiv-cs-cl

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Research

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction

DGX agent

arXiv:2508.13826v4 Announce Type: replace-cross Abstract: Cardiac Magnetic Resonance (CMR) imaging is a critical tool for diagnosing and managing cardiovascular disease, yet its utility is often limit

researcharxiv-cs-cv

27 Jul 2026

LatentFlow: Visual Analytics for Latent Space Analysis in Molecular Graph Neural Networks

arXiv:2607.21941v1 Announce Type: new Abstract: Chemists and materials scientists increasingly use machine learning models, such as graph neural networks (GNNs), to predict properties of molecules and

LayoutLite: Token-Level Implicit Layout Analysis for Efficient Document OCR

arXiv:2607.22200v1 Announce Type: new Abstract: End-to-end OCR systems based on vision-language models have achieved strong performance in complex document OCR, but their efficiency is limited by the

safetyarxiv-cs-cv

Tutorials

Learning Adaptive Semantic Gaussian Allocation for 3D Occupancy

arXiv:2607.21896v1 Announce Type: new Abstract: Semantic 3D Gaussians provide a compact representation for 3D semantic occupancy prediction by rendering semantic primitives into a voxel volume under v

tutorialsarxiv-cs-cv

Tutorials

Learning Diverse Humanoid Tasks via Synthetic Video Scenarios without Real World Data

arXiv:2607.21648v1 Announce Type: new Abstract: The human-like morphology of humanoid robots grants them exceptional potential for agile and versatile motor capabilities, but it also introduces signif

tutorialsarxiv-cs-ro

Leveraging External Knowledge for Historical Document Restoration via Retrieval-Augmented Large Language Models

arXiv:2607.21936v1 Announce Type: new Abstract: Historical documents act as invaluable knowledge archives but often suffer from illegibility due to physical deterioration and damage. While existing re

local-aiarxiv-cs-cl

Local Multimodal Music Alignment from Global Supervision

arXiv:2607.10023v2 Announce Type: replace-cross Abstract: Understanding music requires understanding localized relationships across data modalities, e.g., how time in performance audio maps onto posit

safetyarxiv-cs-lg

Looped Latent Attention: Cross-Loop KV Compression for Looped Transformers

arXiv:2607.15456v2 Announce Type: replace-cross Abstract: Looped, weight-tied Transformers reduce parameters by reusing a single block, but decoding still stores a separate K/V cache for every recurre

Agents

MedKGent: A Large Language Model Agent Framework for Constructing Temporally Evolving Medical Knowledge Graph

arXiv:2508.12393v3 Announce Type: replace Abstract: The rapid expansion of medical literature challenges the scalable structuring of domain knowledge. Knowledge Graphs (KGs) offer a solution, yet curr

agentsarxiv-cs-cl

Applications

Meta-Learning Approaches for Speaker-Dependent Voice Fatigue Models

arXiv:2505.23378v3 Announce Type: replace Abstract: Speaker-dependent modelling can substantially improve performance in speech-based health monitoring applications. While mixed-effect models are comm

applicationsarxiv-cs-lg

MoE^2-LoRA: When MoE Models Meet MoE-style Low-Rank Adaptation

arXiv:2607.21978v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures have been widely adopted in large language models, yet parameter-efficient fine-tuning (PEFT) for MoE models rema

MotifRole-Diff: Risk-Optimal Role-Aware Corruption for Masked Molecular Graph Diffusion

arXiv:2607.21634v1 Announce Type: new Abstract: Masked discrete diffusion for molecular graph generation typically applies a uniform corruption schedule to all tokens in a lossless graph-to-sequence r

Nanbeige4.2-3B: Unlocking Agentic Capabilities in a Compact Mode

arXiv:2607.22083v1 Announce Type: cross Abstract: We present Nanbeige4.2-3B, a compact general agentic model with 3B non-embedding parameters. It delivers strong performance across code-agent, office-

Nice little insights on doing autoresearch with coding agents. Hand a coding agent a dataset, an eval script, one editable file, and no supe…

Nice little insights on doing autoresearch with coding agents. Hand a coding agent a dataset, an eval script, one editable file, and no supervision. That's autoresearch and it tries to optimize the nu

model-releasesdair-ai--x

On the Convergence of Stochastic Low-Rank Adaptation

arXiv:2607.21975v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) optimizes J(B,A)=mathcal L(W_base+sBA) over two adapters B in R^{m imes r} and A in R^{r imes n} that form a low-rank update

One Hand Watches The Other: Dynamic Multi-Agent Cooperation for Sample-Efficient Bimanual Manipulation in Dynamic Environments

model-releasesarxiv-cs-lg

arXiv:2607.22119v1 Announce Type: cross Abstract: Multi-stream robot manipulation policies achieve unparalleled sample efficiency and generalization by modeling actions relative to environmental refer

Opaque Epistemic Mediation: How LLM Deployment Configurations Shape the Validation of Pseudo-Science

arXiv:2607.22513v1 Announce Type: cross Abstract: Commercial large language models are increasingly used as knowledge references, yet their stance on contested scientific claims is neither stable nor

Optimal Transport Image Representation and Deep Covariance Alignment (CORAL) for Control Valve Stiction Detection

model-releasesarxiv-cs-cv

arXiv:2607.22486v1 Announce Type: new Abstract: Control valve stiction is a common cause of unwanted oscillations and poor control-loop performance in industrial processes. Data-driven methods can aut

Physically Constrained Federated Additive Models for O-RAN SLA-Risk Prediction

arXiv:2607.21665v1 Announce Type: new Abstract: Proactive service assurance in O-RAN requires predicting per-slice SLA violations before they occur. The prediction model must be auditable by operators

local-aiarxiv-cs-lg

PinEqualizer: Full Funnel Content Exploration and Debiasing System at Pinterest

arXiv:2607.22518v1 Announce Type: cross Abstract: In this paper, we propose a new solution for addressing the content cold-start problem in industry-scale search and recommender systems. Compared to p

safetyarxiv-cs-lg

Probing Speaker Identity Sensitivity in Audio Deepfake Detectors

arXiv:2607.21820v1 Announce Type: cross Abstract: Audio deepfake detectors are trained to distinguish genuine speech from synthetic speech and often perform well on standard benchmarks. Yet the same d

Tutorials

Quality Text, Robust Vision: The Role of Language in Enhancing Visual Robustness of Vision-Language Models

arXiv:2507.16257v2 Announce Type: replace Abstract: Defending pre-trained vision-language models (VLMs), such as CLIP, against adversarial attacks is crucial, as these models are widely used in divers

tutorialsarxiv-cs-cv

RadSight: Towards Perceptually Reliable Multimodal Radiology Image Understanding

model-releasesarxiv-cs-cv

arXiv:2607.22293v1 Announce Type: new Abstract: Medical multimodal large language models (MLLMs) are increasingly expected to perform complex image understanding tasks, yet their reliability is often

Reliability-Aware Bayesian Optimization of 1310 nm PCSELs with FDTD Verification

arXiv:2607.21772v1 Announce Type: cross Abstract: Near 1310 nm photonic-crystal surface-emitting lasers (PCSELs) are attractive narrow-beam sources for optical communication and sensing, but their fin

local-aiarxiv-cs-lg

Reliability Scales Inversely: Bigger Language Models Compound Mistakes Faster

arXiv:2607.18292v2 Announce Type: replace-cross Abstract: As language models scale, answers start truer but degrade faster: scaling buys capability but erodes reliability. The knowledge-gap account --

Remedying Coarsening-Based GNN Training under Heterophily via Adaptive Complementary Enhancement

arXiv:2607.21885v1 Announce Type: new Abstract: Coarsening-based training for graph neural networks (GNNs), i.e. training on coarsened graphs rather than the original large ones, has become a promisin

Risk-Routed Implicit Boundary Refinement for Robust Ultrasound Image Segmentation

model-releasesarxiv-cs-cv

arXiv:2607.21787v1 Announce Type: new Abstract: Medical ultrasound (US) image segmentation faces significant challenges due to speckle noise, low-contrast boundaries, acoustic shadowing, and acquisiti

Scaling Native Multimodal Pre-Training From Scratch

arXiv:2607.22043v1 Announce Type: new Abstract: Although large language models (LLMs) exhibit remarkable reasoning capabilities, their reliance on text-only pre-training restricts the perception of th

researcharxiv-cs-cl

Hardware

Six Agent Harness Capabilities for Higher Model Performance

The performance of AI agents depends not only on the underlying models but also heavily on their “harness”—the surrounding architecture that supplies context, state management, action execution, and t

hardwarenvidia-developer

Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills

arXiv:2607.22529v1 Announce Type: new Abstract: LLM training is shifting from manual design and annotation to interaction-driven self-evolution. However, existing self-evolutionary methods face a fund

Small Vision-Language Models Know When They Are Wrong But Cannot Say So: A Two-Model Study of Stated versus Internal Confidence Under Realistic Image Degradation

arXiv:2607.22034v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly deployed on consumer hardware where input images are degraded by compression, camera shake, and poor li

researcharxiv-cs-cl

StARS: Socially Appropriate Robot Actions via a Recommender System-Driven Approach

arXiv:2607.21802v1 Announce Type: new Abstract: Social appropriateness in human-robot interaction (HRI) is not universal: different people can judge the same robot action differently in the same situa

researcharxiv-cs-ro

Stop to Decide: Latency-Aware Proprioceptive Navigation Primitives for Mapping-Free Quadruped Inspection

model-releasesarxiv-cs-ro

arXiv:2607.11204v2 Announce Type: replace Abstract: Onboard quadruped inspection systems often share limited compute between perception and navigation, reducing the rate at which event-triggered contr

SurvDiff: A Diffusion Model for Generating Synthetic Data in Survival Analysis

arXiv:2509.22352v3 Announce Type: replace Abstract: Survival analysis is a cornerstone of clinical research by modeling time-to-event outcomes such as metastasis, disease relapse, or patient death. Un

Susceptible Reservoir Architectures for Regime-Conditional Volatility Forecasting

arXiv:2607.22491v1 Announce Type: new Abstract: Volatility forecasting is dominated by persistence and measurement noise, leaving limited residual structure for nonlinear models to exploit. We introdu

Synthetic Speech, Real Signal: Paralinguistic Preservation and Cross-Lingual Augmentation via Voice Cloning

model-releasesarxiv-cs-lg

arXiv:2607.22304v1 Announce Type: new Abstract: Synthetic data augmentation in speech is common practice for linguistic tasks like ASR, but has seen far less work for paralinguistic ones, especially c

TDiR: Transformer based Diffusion for Image Restoration Tasks

arXiv:2506.20302v2 Announce Type: replace Abstract: Images captured in challenging environments often experience various types of degradation, such as noise, color cast, blur, and light scattering. Th

researcharxiv-cs-cv

The Hard Decision Layer: Evidence for Committed Inference in Transformers

arXiv:2607.21613v1 Announce Type: cross Abstract: We investigate where and how transformer-based language models commit to predictions in multiple-choice question answering. We identify the _Hard Deci

The pretraining domain outweighs the training objective in setting the privacy-utility trade-off of differentially private medical image analysis

arXiv:2601.19618v2 Announce Type: replace Abstract: Differential privacy protects the patients whose images train medical imaging models, but it lowers diagnostic accuracy, and the initialization is t

local-aiarxiv-cs-cv

Agents

Towards Reducing Foreign Language Anxiety Using Level-Appropriate Embodied Conversational Agents

arXiv:2607.21887v1 Announce Type: cross Abstract: Foreign language anxiety (FLA) can be a major barrier to second language acquisition (SLA), especially in conversational contexts. With the proliferat

agentsarxiv-cs-cl

Hardware

Unified Static-Dynamic Pruning for Efficient LLM Inference

arXiv:2607.21985v1 Announce Type: cross Abstract: The increasing deployment of large language models (LLMs) has magnified the computational and memory bottlenecks of autoregressive decoding, where low

hardwarearxiv-cs-lg

Hardware

We're proud to join @NVIDIA and the Open Secure AI Alliance. To support open source models, we're contributing our research on measuring the…

We're proud to join @NVIDIA and the Open Secure AI Alliance. To support open source models, we're contributing our research on measuring the trustworthiness and security of open source models. Closing

hardwarecognition-ai--x

What Happens to Accuracy When Photo Lineups Contain Non-Mated Rank-One Images From Large Galleries?

arXiv:2607.21792v1 Announce Type: new Abstract: One-to-many facial identification is commonly used to match a probe image from surveillance video against a gallery of driver's licenses and/or booking

researcharxiv-cs-cv

When Ethics and Payoffs Diverge: LLM Agents in Morally Charged Social Dilemmas

arXiv:2505.19212v2 Announce Type: replace Abstract: Recent advances in LLMs have enabled their use in complex agentic roles, involving decision-making with humans or other agents, making ethical align

100B Models on Cheap Hardware: how realistic and limitations

There is a lot of buzz around running 100B parameter models on cheap local hardware using ternary (1.58-bit) quantization like Microsoft's BitNet architecture. The theoretical hardware shortcuts are i

model-releasesr-ollama

26 Jul 2026

I want to use AI coding agents for machine learning projects [D]

model-releasesr-machinelearning

I'm a software engineer who mainly builds softwaes/applications, and I'm starting to work on machine learning projects. Since ML workloads often require GPUs, I know services like Google Colab and Kag

26 Jul 2026

Teaching LLMs to Update Beliefs for Efficient Long-Horizon Interaction