Search: “evaluation”

SafeECGMatch: Calibration-Aware Joint Frequency and Time Space Semi-Supervised Learning for Open-Set ECG Classification

arXiv:2606.08037v1 Announce Type: cross Abstract: Electrocardiogram (ECG) classification models often suffer from severe label scarcity, making semi-supervised learning (SSL) an attractive strategy fo

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Model Releases

SC3: The Multi-Solvent Solubility Challenge and Benchmark

DGX agent

arXiv:2606.07656v1 Announce Type: cross Abstract: Solubility prediction is a standard benchmark in computational chemistry, yet multi-solvent models which reportedly approach the experimental-noise ce

model-releasesarxiv-cs-lg

9 Jun 2026

Scaling Decision-Focused Learning to Large Problems with Lagrangian Decomposition

arXiv:2606.08797v1 Announce Type: cross Abstract: Decision-focused learning has shown great promise for addressing predict-then-optimize problems, particularly in the presence of under-specified model

scCBGM: Interpretable Single-Cell Counterfactual Editing

arXiv:2606.07760v1 Announce Type: new Abstract: Understanding cellular phenotypes and how they respond to perturbations is critical for disease biology and therapeutic design. Single-cell RNA sequenci

SciTrace: Trajectory-Aware Safety Reasoning for Scientific Discovery Agents

arXiv:2606.08234v1 Announce Type: new Abstract: LLM-based scientific agents have shown strong capacity for autonomous research, yet their safety layers remain structurally divorced from core reasoning

Securing Self-supervised Data Curation for Foundation Models Robustness

arXiv:2606.09511v1 Announce Type: new Abstract: Self-supervised data curation provides a pathway to scaling and improving the generalization capabilities of machine learning models. By leveraging self

Seeing the Hivemind: A Consensus-Aware Interaction Technique for Mitigating AI Homogenization

arXiv:2606.09587v1 Announce Type: cross Abstract: People are increasingly using AI for creative tasks such as writing. While adoption continues to grow, this form of use risks undermining individual c

local-aiarxiv-cs-ai

SegmentAnyTreeV2: Scaling Transformer-Based Tree Instance Segmentation Across Sensors, Platforms, and Forests

model-releasesarxiv-cs-cv

arXiv:2606.08206v1 Announce Type: new Abstract: We present SegmentAnyTreeV2, a sensor- and platform-agnostic framework for semantic and instance segmentation of forest point clouds. The model combines

Self-Supervised Learning with a Multi-Task Latent Space Objective

arXiv:2602.05845v2 Announce Type: replace Abstract: We propose a multi-task formulation of self-predictive Siamese SSL in which each spatial transformation defines a distinct latent-space alignment ta

safetyarxiv-cs-cv

Semantic Quorum Assurance: Collective Certification for Non-Deterministic AI Infrastructure

arXiv:2606.08021v1 Announce Type: cross Abstract: As large language model (LLM) agents are integrated into autonomous cloud operations, distributed systems face a semantic reliability problem: propose

SENTRY: Statistical Reliability Analysis of Vision Transformers Under Soft Errors

arXiv:2606.07620v1 Announce Type: cross Abstract: With the growth of Vision Transformers in safety-critical domains like autonomous systems and medical imaging, ensuring their reliability against soft

Agents

Shape Formation for the Cooperative Transportation of Arbitrary Objects Using Multi-Agent Reinforcement Learning

arXiv:2606.09610v1 Announce Type: cross Abstract: Cooperative object transportation is essential in numerous domains, including industrial to domestic services. A popular transportation strategy is to

agentsarxiv-cs-ai

Shared Semantics, Divergent Mechanisms: Unsupervised Feature Discovery by Aligning Semantics and Mechanisms

arXiv:2606.08236v1 Announce Type: cross Abstract: As large language models are increasingly deployed in high-stakes settings, there is a growing need for tools that audit not only model outputs but al

Agents

SIGA: Self-Evolving Coding-Agent Adapters for Scientific Simulation

arXiv:2606.09774v1 Announce Type: new Abstract: Advanced scientific simulators expose specialized input languages that turn simulation goals into executable configurations, but learning them can cost

agentsarxiv-cs-ai

Signals Are Not States: Neuro-Symbolic Safeguards for Culturally Aware Classroom AI

arXiv:2603.22793v2 Announce Type: replace Abstract: Classroom AI systems increasingly infer high-level educational states such as engagement, confusion, collaboration, participation, and instructional

Applications

Simultaneous hyperkinetic movement disorders phenotyping: a cross-cohort pediatric transfer study using routine videos, markerless pose estimation and a tabular foundation model

arXiv:2606.07674v1 Announce Type: new Abstract: Objective: To develop and externally test a video-based framework for simultaneous detection of hyperkinetic MDs phenomenologies: dystonia, tremor, myoc

applicationsarxiv-cs-cv

SMART: Shot-Aware Multimodal Video Moment Retrieval with Audio-Enhanced MLLM

arXiv:2511.14143v2 Announce Type: replace-cross Abstract: Video Moment Retrieval is a task in video understanding that aims to localize a specific temporal segment in an untrimmed video based on a nat

local-aiarxiv-cs-ai

Tutorials

SmartMixed: A Two-Phase Training Strategy for Adaptive Activation Function Learning in Neural Networks

arXiv:2510.22450v3 Announce Type: replace-cross Abstract: The choice of activation function plays a critical role in neural networks, yet most architectures still rely on fixed, uniform activation fun

tutorialsarxiv-cs-ai

SMI: Efficient Self-Supervised Learning via Mutual-Information-Inspired Dependency Optimization

arXiv:2606.08332v1 Announce Type: new Abstract: Self-supervised learning (SSL) has achieved remarkable representation learning performance, but many existing methods rely on large batch sizes, memory

safetyarxiv-cs-cv

SNN-MLIR: An MLIR Dialect for Compiling Neuromorphic SNNs from NIR to Bare-Metal C

arXiv:2606.09213v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) are increasingly trained in a wide range of frameworks (SnnTorch, Lava, Norse, and others) each with its own model form

Hardware

SoccerNet 2026 Player-Centric Ball-Action Spotting:Retraining and Post-Processing Extensions to the FOOTPASS Baselines

arXiv:2606.09679v1 Announce Type: new Abstract: We describe our system for the SoccerNet 2026 Player-Centric Ball-Action Spotting Challenge, which requires predicting who performs which action and whe

hardwarearxiv-cs-cv

SoK: Reconstruction Attacks on Synthetic Tabular Data (Insights from Winning the NIST CRC)

arXiv:2606.08372v1 Announce Type: cross Abstract: Synthetic data is increasingly promoted as a privacy-preserving substitute for releasing sensitive tabular records, yet its central adversarial threat

Solving Inverse Problems with Flow-based Models via Model Predictive Control

arXiv:2601.23231v2 Announce Type: replace-cross Abstract: Flow-based generative models provide strong unconditional priors for inverse problems, but guiding their dynamics for conditional generation r

Speaker-Invariant Representation Learning for Spoofing Detection via Gradient Reversal and A Variational Information Bottleneck

arXiv:2606.08678v1 Announce Type: cross Abstract: Sophisticated generative speech technology can undermined the reliability of voice biometrics. While spoofing detection systems excel when assessed un

safetyarxiv-cs-lg

Tutorials

SpectraLDS: Provable Distillation for Linear Dynamical Systems

arXiv:2505.17868v2 Announce Type: replace Abstract: We present the first provable method for identifying symmetric linear dynamical systems (LDS) with accuracy guarantees that are independent of the s

tutorialsarxiv-cs-lg

SPIN: Decentralized Swarm Control via Tensorized Policy Coordination

arXiv:2606.07557v1 Announce Type: new Abstract: Decentralized multi-agent swarm coordination on resource-constrained edge platforms remains fundamentally bottlenecked by the exponential scaling of joi

safetyarxiv-cs-lg

Stable and Scalable Probabilistic Numerical Solvers for Stiff and High-Dimensional ODEs

arXiv:2606.08203v1 Announce Type: cross Abstract: Filtering-based probabilistic numerical solvers for ordinary differential equations (ODEs) have been established as a flexible and efficient simulatio

Hardware

STAR-KV: Low-Rank KV Cache Compression via Soft Thresholding for Adaptive Rank Control

arXiv:2606.08382v1 Announce Type: cross Abstract: Low-rank projection has emerged as a promising approach for compressing the KV cache by exploiting hidden-dimension redundancy. However, prior methods

hardwarearxiv-cs-ai

STAR: Rethinking MoE Routing as Structure-Aware Subspace Learning

arXiv:2606.08814v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) scales model capacity efficiently by selectively routing inputs to a specialized subset of experts. However, input-expert speci

Steer Where It Matters: Token-Level Visual-Sensitivity Steering for LVLMs Hallucination Mitigation

arXiv:2606.07647v1 Announce Type: new Abstract: Large vision language models (LVLMs) have made rapid advancements and are deployed across various applications, yet hallucinations remain a major challe

Stochastic Dimension Implicit Functional Projections for Global Integral Conservation in High-Dimensional PINNs

arXiv:2603.29237v2 Announce Type: replace Abstract: Enforcing prescribed global integral constraints in mesh-free neural PDE solvers is challenging in high-dimensional domains. Existing projection met

Strained Coherence: A Pre-Failure Signal in Coding Agent Execution Trajectories

arXiv:2606.07889v1 Announce Type: cross Abstract: LLM-based coding agents sometimes acknowledge a problem in their own reasoning and then proceed anyway. We call this pattern strained coherence: a saf

Structure-Aware Modeling of Multiple-Choice Questions Improves Automatic Difficulty Estimation

arXiv:2606.08988v1 Announce Type: cross Abstract: Automatic Question Difficulty Estimation (AQDE) holds growing promise for educational assessment because it has the potential to yield difficulty esti

Structured Neuron Pruning in Deep Neural Networks Using Multi-Armed Bandits

arXiv:2606.07615v1 Announce Type: cross Abstract: Deep neural networks often contain redundant hidden units. Removing individual weights can reduce parameter count, but unstructured sparsity is not al

Summarization is Not Dead Yet

arXiv:2606.08000v1 Announce Type: cross Abstract: The progress of large language models (LLMs) has fueled claims that model-generated summaries rival or even surpass human-written references, raising

Sycophancy as a Multilingual Alignment Failure: How Safety Degrades Across Languages, Topics, and Models

arXiv:2606.08451v1 Announce Type: cross Abstract: Safety-aligned large language models often exhibit sycophancy, which is the tendency to affirm users' opinions regardless of factual accuracy. Althoug

SynthICL: Scalable In-context Imitation Learning with Synthetic Data

arXiv:2606.08154v1 Announce Type: new Abstract: In-context imitation learning (ICIL) enables robots to learn new tasks from a small number of demonstrations by conditioning a pre-trained policy on tas

safetyarxiv-cs-ro

Systematic LLM Translation of Legacy Scientific Code to Differentiable Frameworks: Application to a Land Surface Model

arXiv:2606.07681v1 Announce Type: cross Abstract: Differentiable programming offers transformative capabilities for scientific modeling, enabling gradient-based parameter estimation, sensitivity analy

TeamHerald@CHIPSAL 2026: Hate Speech Detection and Sentiment Analysis of Nepali Memes using Transformer-based Architectures and Ensemble Learning

arXiv:2606.08770v1 Announce Type: cross Abstract: The analysis of internet memes in the Nepali language is complicated by frequent code-mixing and a lack of established baseline resources. While memes

Temporal-Aware Reasoning Optimization for Video Temporal Grounding

arXiv:2606.09248v1 Announce Type: new Abstract: Multi-modal Large Language Models (MLLMs) have achieved remarkable progress in video temporal grounding with reinforcement learning for generating reaso

local-aiarxiv-cs-cv

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning

arXiv:2606.08231v1 Announce Type: new Abstract: Test-time Scaling (TTS) has emerged as a pivotal research direction for enhancing model performance by dynamically allocating computational resources du

The Last Visible Pixel: Probing Fine-Scale Perception in Vision-Language Models

arXiv:2606.07861v1 Announce Type: cross Abstract: Recent vision-language models (VLMs) excel at multimodal understanding and reasoning, yet their fine-grained visual perception remains underexplored.

The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward Passes

arXiv:2402.08922v3 Announce Type: replace Abstract: Large-scale black-box models have become ubiquitous across numerous applications. Understanding the influence of individual training data sources on

The Montparnasse Algorithm for RNA Design

arXiv:2606.07562v1 Announce Type: cross Abstract: RNA design consists of discovering a nucleotide sequence that optimizes predefined criteria, such as secondary structure. It is useful for synthetic b

The Need for Neural ISP in the Small-Pixel Era: How Shrinking Pixels Push Optics to the Limit and Neural Restoration Pushes Back

arXiv:2606.07675v1 Announce Type: cross Abstract: Smartphone telephoto cameras are approaching a 'telephoto physics wall': as pixel pitches shrink toward sub-0.5 micron, the optics remain limited by g

local-aiarxiv-cs-cv

The Value of Personalized Recommendations: Evidence from Netflix

arXiv:2511.07280v5 Announce Type: replace-cross Abstract: Personalized recommendation systems shape much of user choice online, yet their targeted nature makes separating out the value of recommendati

TIDE: Task-Isolated Diffusion for Unified Video Editing and Generation

arXiv:2606.08260v1 Announce Type: new Abstract: Recent advances in Diffusion Transformers have driven rapid progress in video generation and editing, yet these capabilities are still handled by separa

Agents

To Nuke or Not to Nuke: LLMs' (Missing) Ethical Reasoning and Actions in a High-Stakes Decision-Making Simulation

arXiv:2606.08310v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as long-horizon agents with decision-making capacities. While LLMs can show ethical competence on

agentsarxiv-cs-ai