Search: “evaluation”

Machine Learning Methods for Studying Latent Neural Activity Dynamics

arXiv:2606.10530v1 Announce Type: cross Abstract: Recent developments in brain recording are driving a demand for machine learning tools capable of decoding the latent structure of large populations o

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Magnetic HIP-NN for spin dynamics in disordered itinerant magnets

DGX agent

arXiv:2606.10349v1 Announce Type: cross Abstract: We present a magnetic extension of the Hierarchically Interacting Particle Neural Network (HIP-NN) that enables large-scale simulations of electron-me

model-releasesarxiv-cs-lg

10 Jun 2026

Measuring Human Value Expression in Social Media Texts: Calibrated LLM Annotation and Encoder Transfer

arXiv:2606.11018v1 Announce Type: new Abstract: Measuring subjective constructs in naturally occurring social media text requires annotation procedures that are theoretically grounded, empirically val

safetyarxiv-cs-cl

MedFeat: Model-Aware and Explainability-Driven Feature Engineering with LLMs for Clinical Tabular Prediction

arXiv:2603.02221v2 Announce Type: replace-cross Abstract: In clinical tabular prediction, classical machine learning models with feature engineering often outperform neural methods. LLMs are increasin

MetaPlate: Counterfactual-Guided RAG-LLM Tool for Personalized Food Recommendation and Hyperglycemia Prevention

arXiv:2606.10120v1 Announce Type: cross Abstract: Postprandial hyperglycemia is a key risk factor for metabolic disorders; however, existing dietary guidance is often static, impractical, and insuffic

Mind the Gap: Can Frontier LLMs Pass a Standardized Office Proficiency Exam?

arXiv:2606.10956v1 Announce Type: new Abstract: The deployment of Large Language Model (LLM) agents for computer automation is accelerating, yet their ability to navigate complex, professional-grade p

Local Ai

MinhwaNet: Faithful but Insufficient Object Grounding in Korean Folk Painting

arXiv:2606.09855v1 Announce Type: cross Abstract: Korean folk painting (minhwa) is built from a small vocabulary of auspicious symbols, a tiger for protection, a pair of birds for marital harmony, a p

local-aiarxiv-cs-cv

MIRAGE: A Polarity-Flipping Encoding Subspace in LLM Agents

arXiv:2606.10304v1 Announce Type: new Abstract: When LLM agents are coerced into covertly encoding sensitive data (Base64, ROT13, acrostic, synonym chains, and beyond), the resulting outputs evade out

Mitigating Bias in Low-SNR Financial Reinforcement Learning via Quantum Representations

arXiv:2606.10448v1 Announce Type: cross Abstract: The financial market is a typical low signal-to-noise ratio (SNR) setting, which often destabilizes off-policy maximum-entropy methods like Soft Actor

Mix, Don't Pick: Why Synthetic Corpus Composition Matters for Time Series Foundation Model Pretraining

arXiv:2606.09912v1 Announce Type: cross Abstract: Choosing the wrong synthetic generator for time-series foundation model pretraining is costly: under identical training budgets, the best and worst ge

Mixtures of Neural Operators Reduce Active Complexity in Operator Learning

arXiv:2404.09101v3 Announce Type: replace-cross Abstract: Operator-learning systems are not governed solely by total parameter count; for one query, the relevant bottleneck can be the model that must

mlr3mbo: Bayesian Optimization in R

arXiv:2603.29730v2 Announce Type: replace-cross Abstract: We present mlr3mbo, a modular toolbox for Bayesian optimization in R. mlr3mbo supports single- and multi-objective optimization, multi-point p

More Human or More AI? Visualizing Human-AI Collaboration Disclosures in Journalistic News Production

arXiv:2601.11072v1 Announce Type: cross Abstract: Within journalistic editorial processes, disclosing AI usage is currently limited to simplistic labels, which misses the nuance of how humans and AI c

applicationsarxiv-cs-ai

Multi-UAV Active Sensing with Information Gain-based Planning and Belief Fusion

arXiv:2606.10986v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) are increasingly used for active sensing and information gathering in spatially distributed environments. Their performa

applicationsarxiv-cs-ro

MV-Actor: Aligning Multi-View Semantics and Spatial Awareness for Bimanual Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.10899v1 Announce Type: new Abstract: Robotic manipulation has been widely applied in industrial scenarios. Compared with single-arm manipulation, bimanual manipulation is equipped with mult

N-GRPO: Embedding-Level Neighbor Mixing for Enhanced Policy Optimization

arXiv:2606.10768v1 Announce Type: cross Abstract: The success of Large Language Models in mathematical reasoning relies heavily on the generation of diverse and valid solution paths during the rollout

Next Forcing: Causal World Modeling with Multi-Chunk Prediction

model-releasesarxiv-cs-cv

arXiv:2606.11187v1 Announce Type: new Abstract: Autoregressive video generation has emerged as a powerful paradigm for World Action Models (WAMs). However, existing approaches suffer from slow trainin

++nnU-Net: Scaling nnU-Net with Prefix-Based Data Augmentation

arXiv:2606.10713v1 Announce Type: cross Abstract: The nnU-Net has demonstrated continuous success in medical segmentation tasks, which heavily rely on the availability and diversity of annotated biome

NoiseSDF2NoiseSDF: Learning Clean Neural Fields from Noisy Supervision

arXiv:2507.13595v3 Announce Type: replace Abstract: Reconstructing accurate implicit surface representations from point clouds remains a challenging task, particularly when data is captured using low-

researcharxiv-cs-cv

Nonlinear Estimator: Dual Bayesian Affine Estimators for Parameter Learning

arXiv:2606.10111v1 Announce Type: new Abstract: This paper presents a nonlinear parameter estimator for Wiener-type state-space models obtained as a fixed-point architecture that couples two affine mi

ObjSplat: Geometry-Aware Gaussian Surfels for Active Object Reconstruction

arXiv:2601.06997v2 Announce Type: replace-cross Abstract: Autonomous high-fidelity object reconstruction is fundamental for creating digital assets and bridging the simulation-to-reality gap in roboti

agentsarxiv-cs-cv

One Step Closer to Ground Truth: A Multi-Scale Residual-Aware Representation Learning Pipeline for Predicting Time Series Data

arXiv:2606.10678v1 Announce Type: new Abstract: Transformer-based models have emerged as leading paradigms in time-series forecasting in recent years, employing self-attention mechanisms to capture lo

One Token per Multimodal Evidence: Latent Memory for Resource-Constrained QA

arXiv:2606.10572v1 Announce Type: new Abstract: External memory effectively grounds large language models (LLMs) and vision-language models (VLMs)-based question answering (QA) in relevant multimodal

Overcoming Rank Collapse in Feedback Alignment

arXiv:2606.11123v1 Announce Type: new Abstract: Backpropagation (BP) is widely viewed as biologically implausible, in part because it requires feedback weights to be the transpose of forward weights f

Parallel Causal Associative Fields: Gated Sparse Memory for Long-Context Language Modeling

arXiv:2606.10435v1 Announce Type: cross Abstract: Transformers achieve strong language modeling performance by providing direct token-to-token communication paths, but causal self-attention scales qua

Local Ai

PatchSTG: Scalable Spatiotemporal Graph Transformers for Traffic Forecasting on Irregular Sensor Networks

arXiv:2606.09872v1 Announce Type: cross Abstract: Traffic forecasting is a fundamental component of intelligent transportation systems, yet remains challenging in real-world settings due to irregular

local-aiarxiv-cs-ai

PathRelax: Parallel-Path Relaxed Speculative Jacobi Decoding for Accelerating Auto-Regressive Text-to-Image Generation

arXiv:2606.10492v1 Announce Type: new Abstract: The growing need for high-resolution image generation in autoregressive text-to-image models has resulted in extended token sequences, significantly inc

researcharxiv-cs-cv

PhantomBench: Benchmarking the Non-existential Threat of Language Models

arXiv:2606.11105v1 Announce Type: cross Abstract: Hallucinations, where language models (LMs) generate factually ungrounded responses, pose serious risks, as users tend to blindly rely on them. This i

Pose-ICL: 3D-Aware In-Context Learning for Pose-Controllable Subject Customization

arXiv:2606.10902v1 Announce Type: cross Abstract: Subject Customization is a foundational task in modern image generation. By providing a few reference images and a text prompt, users can generate ima

applicationsarxiv-cs-ai

PreAct-Bench: Benchmarking Predictive Monitoring in LLMs

arXiv:2606.09890v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents capable of executing multi-step action trajectories toward a given objecti

Predicting Future Behaviors in Reasoning Models Enables Better Steering

arXiv:2606.11172v1 Announce Type: new Abstract: Deployed large reasoning models (LRMs) often behave unexpectedly. Test-time steering controls LRM outputs by intervening on their hidden representations

researcharxiv-cs-lg

Privacy-Preserving Credit Risk Prediction with Alternative Data

arXiv:2606.10333v1 Announce Type: new Abstract: Credit risk prediction is a critical problem in the consumer credit industry. Traditionally, financial institutions construct credit risk prediction mod

applicationsarxiv-cs-lg

Profy: Interpretable Visualization of Expertise-Dependent Motor Skills Toward Supporting Piano Practice

arXiv:2606.10627v1 Announce Type: cross Abstract: The quality of piano performance depends on nuanced timing, articulation, and dynamic control, but practice feedback is often summary-based and hard t

researcharxiv-cs-lg

Pushing the Limits of LLM Tool Calling via Experiential Knowledge Integration and Activation

arXiv:2606.10875v1 Announce Type: new Abstract: Large language models (LLMs) rely on tool use to act as autonomous agents, yet often fail in multi-step execution due to insufficient tool-related knowl

agentsarxiv-cs-cl

Pushing the Performance Limits in Autonomous Racing: Continuous Stability-Aware Adaptive Velocity Planning in Formula Student Driverless

arXiv:2606.10733v1 Announce Type: new Abstract: In autonomous racing, especially in competitions such as Formula Student Driverless, precise planning of the target velocity of a race car is crucial fo

agentsarxiv-cs-ro

Quality Is Not a Safety Proxy Under Quantization

arXiv:2606.10154v1 Announce Type: new Abstract: Quantized checkpoints are often screened first with quality metrics and only later, if at all, with direct safety tests. This paper audits that shortcut

REAL: A Reasoning-Enhanced Graph Framework for Long-Term Memory Management of LLMs

arXiv:2606.10694v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly expected to interact with users over long time horizons. However, due to their finite context window, LLMs

ReasonAlloc: Hierarchical Decoding-Time KV Cache Budget Allocation for Reasoning Models

arXiv:2606.11164v1 Announce Type: new Abstract: Long chain-of-thought (CoT) trajectories in large language model (LLM) reasoning cause severe inference bottlenecks due to rapid key-value (KV) cache gr

Reasoning over Semantic IDs Enhances Generative Recommendation

arXiv:2603.23183v2 Announce Type: replace-cross Abstract: Recent advances in generative recommendation have leveraged pretrained LLMs by formulating sequential recommendation as autoregressive generat

RedAct: Redacting Agent Capability Traces for Procedural Skill Protection

arXiv:2606.10813v1 Announce Type: cross Abstract: Users rely on execution traces to observe agent behavior, diagnose failures, and ensure accountability. These traces contain rich procedural detail, i

Resilient Navigation for Autonomous Farm Robots by Leveraging Jerk-Augmented Models with IMU-Only Disturbance Rejection

arXiv:2606.10971v1 Announce Type: new Abstract: Precise state estimation for navigation of autonomous agricultural robots is often compromised by sensor outages (GNSS/LiDAR/Visual) and high-frequency

agentsarxiv-cs-ro

RKSC: Reasoning-Aware KV Cache Sharing and Confident Early Exit for Multi-Step LLM Inference

arXiv:2606.09937v1 Announce Type: cross Abstract: We introduce RKSC (Reasoning-Aware KV Cache Sharing), a training-free inference framework that eliminates two structural redundancies in multi-branch

RobotEQ: Transitioning from Passive Intelligence to Active Intelligence in Embodied AI

model-releasesarxiv-cs-ro

arXiv:2605.06234v2 Announce Type: replace Abstract: Embodied AI is a prominent research topic in both academia and industry. Current research centers on completing tasks based on explicit user instruc

Rotate2Think: Geometric Priming via Orthogonal Rotation to Improve Language Model Reasoning

arXiv:2606.09873v1 Announce Type: cross Abstract: Reasoning models achieve strong performance on challenging tasks by generating explicit intermediate reasoning traces before producing a final answer.

SAFE: An LLM-as-Verifier Framework for Evidence-Grounded Multi-Hop Reasoning

arXiv:2604.01993v2 Announce Type: replace-cross Abstract: Multi-hop QA benchmarks often reward Large Language Models (LLMs) for spurious correctness, where models reach correct answers through invalid

Schmidt Decomposition-Based Methods for Efficient Quantum Image Encoding

arXiv:2606.10874v1 Announce Type: new Abstract: In quantum image processing, a fundamental step is encoding classical image data into quantum states. This can be achieved using methods such as Flexibl

researcharxiv-cs-cv

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation

arXiv:2606.09871v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) and its variants, originally developed for Large Language Models (LLMs), have recently been applied to Multi

Selection, Not Salience: The Shape and Limits of Personalization in Social Highlighting

arXiv:2606.10398v1 Announce Type: cross Abstract: Does personalizing what a reader sees pay off, and where does it stop? Using a social web highlighter and a co-readership identity control (the same d

safetyarxiv-cs-cl