Search: “models”

GEESE: Genotype-aware End-to-End Spatio-temporal Embedding for Behavioral Phenotyping

arXiv:2605.24370v1 Announce Type: new Abstract: Behavioral phenotyping of genetic animal models currently requires labor-intensive manual feature engineering that limits reproducibility and scalabilit

researcharxiv-cs-lg

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GL-LFGNN:A Global-Local Dual-branch Causal Graph Neural Network Based on Liang-Kleeman Information Flow for EEG Emotion Recognition

DGX agent

arXiv:2605.25061v1 Announce Type: cross Abstract: EEG-based emotion recognition holds significant promise for objective diagnosis of mood disorders. Graph neural networks (GNNs) have emerged as the do

model-releasesarxiv-cs-ai

26 May 2026

Grow-Prune-Freeze Networks: Adaptive & Continual Learning Technique for Olfactory Navigation

arXiv:2605.25170v1 Announce Type: cross Abstract: Training data for olfaction is scattered through disparate, non-standardized datasets that limit the ability to build representative world models. Olf

Improved Scaling Laws via Weak-to-Strong Generalization in Random Feature Ridge Regression

arXiv:2603.05691v2 Announce Type: replace Abstract: It is increasingly common in machine learning to use learned models to label data and then employ such data to train more capable models. The phenom

safetyarxiv-cs-lg

Investigating the Interplay between Contextual and Parametric Chain-of-Thought Faithfulness under Optimization

arXiv:2605.24960v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) faithfulness, i.e., whether CoTs genuinely reflect large language models' (LLM) underlying behavior, is typically evaluated und

Is GPT-4o mini Blinded by its Own Safety Filters? Exposing the Multimodal-to-Unimodal Bottleneck in Hate Speech Detection

arXiv:2509.13608v2 Announce Type: replace Abstract: As Large Multimodal Models (LMMs) become integral to daily digital life, understanding their safety architectures is a critical problem for AI Align

safetyarxiv-cs-lg

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition

arXiv:2411.09816v4 Announce Type: replace Abstract: Large neural networks achieve state-of-the-art performance on many tasks, yet their sheer size hinders deployment on resource-constrained devices. A

LiveMCP-101: Stress Testing and Diagnosing MCP-enabled Agents on Challenging Queries

arXiv:2508.15760v2 Announce Type: replace-cross Abstract: Tool calling has emerged as a critical capability for AI agents. In contrast to conventional tool calling frameworks that rely on static, prov

Applications

Manifold-Constrained MPPI: Real-Time Sampling-Based Control Under Hard Constraints

arXiv:2605.24813v1 Announce Type: new Abstract: Sampling-based model predictive control methods, such as Model Predictive Path Integral (MPPI), offer derivative-free optimization and robustness in com

applicationsarxiv-cs-ro

Measuring the Depth of LLM Unlearning via Activation Patching

arXiv:2605.24614v1 Announce Type: cross Abstract: Large language model (LLM) unlearning has emerged as a crucial post-hoc mechanism for privacy protection and AI safety, yet auditing whether target kn

MEDAL: Manifold Embedding Distillation via Autoencoder Learning

arXiv:2605.24244v1 Announce Type: cross Abstract: Low-dimensional embeddings are widely used as visual summaries of high-dimensional data and to enable downstream scientific discoveries. Yet, popular

MuJoCoUni:Persistent Batched Runtime Primitives for MuJoCo

model-releasesarxiv-cs-ro

arXiv:2605.24922v1 Announce Type: new Abstract: We present MuJoCoUni, a downstream MuJoCo distribution for online robot learning and batched physics evaluation. Alongside the open-loop batched traject

Multimodality Stacking with Blockwise missing values and application to the PIONeeR biomarkers study for prediction of resistance to immunotherapy

arXiv:2605.25050v1 Announce Type: cross Abstract: Integrating multimodal datasets in clinical oncology is frequently hindered by high dimensionality and blockwise missingness, where entire data source

researcharxiv-cs-lg

Local Ai

Multiscale Real-Time Object Detection in the NMS-Free Era: A Comparative Performance Evaluation of YOLOv8 and YOLO26

arXiv:2605.24831v1 Announce Type: cross Abstract: Non-Maximum Suppression (NMS) remains a key post-processing step in many real-time object detection pipelines, but it can introduce latency variation

local-aiarxiv-cs-ai

Neural Integral Operators for Inverse Problems: An Operator-Learning Framework for Small-Sample Spectroscopic Classification

arXiv:2505.03677v3 Announce Type: replace Abstract: Learning maps between function spaces with a strong inductive bias is a central challenge in soft computing, especially when training data are scarc

NeurIPS: Neuro-anatomical Inductive Priors for Sphere-based Brain Decoding

arXiv:2605.24993v1 Announce Type: new Abstract: Current fMRI decoders face a performance-fidelity trade-off where efficient ID encoders outperform geometrically faithful surface-based models. We argue

researcharxiv-cs-ai

OASIS: Observation-Action Space Alignment via SE(3) Trajectory Prediction for Robotic Manipulation

arXiv:2605.25829v1 Announce Type: cross Abstract: Recent vision-language-action (VLA) models and world action models (WAMs) advance robotic manipulation by enriching intermediate representations with

OSDTW: Optimal Shared Depth and Task Weighting for Long-Tailed Recognition

arXiv:2605.24969v1 Announce Type: cross Abstract: Long-tailed recognition suffers from a persistent head--tail trade-off: improving tail performance often degrades head accuracy and can increase train

Parameter Efficient Multi-Class Intelligent Scheduling for Multimodal Online Distributed Industrial Anomaly Detection

arXiv:2605.23984v1 Announce Type: cross Abstract: Industrial anomaly detection has attracted significant attention as a fundamental challenge in industrial systems. The rapid advancement of heterogene

PDEInvBench: A Comprehensive Dataset and Design Space Exploration of Neural Networks for PDE Inverse Problems

arXiv:2605.25353v1 Announce Type: new Abstract: Inverse problems in partial differential equations (PDEs) involve estimating the physical parameters of a system from observed spatiotemporal solution f

Physen-Noise2Noise: Physics-Guided Self-Supervised Defocus Deblurring with Bias Correction under Low-Light Conditions

arXiv:2605.24590v1 Announce Type: cross Abstract: Low-light, long-exposure defocus deblurring remains a challenging problem due to the simultaneous presence of severe blur and complex biased noise. Ex

Pragmatic Reasoning improves LLM Code Generation

arXiv:2502.15835v5 Announce Type: replace-cross Abstract: Pragmatic reasoning helps interlocutors infer intended meaning from ambiguous or underspecified messages by considering shared context and cou

QUEST: Training Frontier Deep Research Agents with Fully Synthetic Tasks

model-releasesarxiv-cs-cl

arXiv:2605.24218v1 Announce Type: new Abstract: Deep research agents extend the role of search engines from retrieving keyword-matched pages to synthesizing knowledge, fundamentally changing how human

Reading, Not Thinking: Understanding and Bridging the Modality Gap When Text Becomes Pixels in Multimodal LLMs

arXiv:2603.09095v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) can process text presented as images, yet they often perform worse than when the same content is provided a

safetyarxiv-cs-cl

Residual Drift Dominates Contradiction in Multi-Turn Constraint Reasoning

arXiv:2605.23940v1 Announce Type: new Abstract: How do multi-turn reasoning systems fail? The expected answer is logical contradiction, in which the system's maintained state becomes unsatisfiable. We

RoboManipBaselines: A Unified Framework for Imitation Learning in Robotic Manipulation across Real and Simulation Environments

model-releasesarxiv-cs-ro

arXiv:2509.17057v3 Announce Type: replace Abstract: We present RoboManipBaselines, an open-source software framework for imitation learning research in robotic manipulation. The framework supports the

Robust Fuzzy Multi-view Learning under View Conflict

arXiv:2605.24475v1 Announce Type: cross Abstract: Trusted multi-view classification aims to deliver reliable fusion for accurate predictions and has recently attracted substantial attention in both ac

Spectral Probe-Circuits: A Three-Step Recipe for Identifying Attention-Head Circuits in Pretrained Transformers

arXiv:2605.24059v1 Announce Type: cross Abstract: We present a three-step recipe for identifying attention-head circuits in pretrained transformers. A per-head spectral signal -- the time-integrated p

TapSampling: Inference-Time Sampling with a Task-Progress-Understanding Verifier for Robotic Manipulation

arXiv:2605.25547v1 Announce Type: new Abstract: Existing embodied control research demonstrates remarkable performance improvements by scaling training data and model size. We instead explore inferenc

safetyarxiv-cs-ro

The Concept Allocation Zone: Tracking How Concepts Form Across Transformer Depth

arXiv:2605.24856v1 Announce Type: cross Abstract: Concept formation in transformer language models is depth-extended, not a single-layer event: concepts emerge gradually across a contiguous region of

Uni-DPO: A Unified Paradigm for Dynamic Preference Optimization of LLMs

arXiv:2506.10054v4 Announce Type: replace-cross Abstract: Direct Preference Optimization (DPO) has emerged as a cornerstone of reinforcement learning from human feedback (RLHF) due to its simplicity a

Applications

VectorArk: Learning Practical Image Vectorization with Rounded Polygon Representation

arXiv:2605.24398v1 Announce Type: cross Abstract: Recent vision-language model (VLM)-based approaches have achieved impressive results on image vectorization tasks. However, they are typically evaluat

applicationsarxiv-cs-ai

WhoSaidIt: Human-LLM Collaborative Annotation for Text-Based Multilingual Speaker-Attribute Classification

model-releasesarxiv-cs-cl

arXiv:2605.26070v1 Announce Type: new Abstract: Annotating speaker attributes from text is inherently ambiguous, particularly in multilingual settings where demographic and social cues are implicit an

AI Evaluation Should Require Standardized Item-Level Data Releases

arXiv:2604.03244v2 Announce Type: replace Abstract: This position paper argues that standardized item-level benchmark data should become the default infrastructure for AI evaluation. Current evaluatio

ALIVE: Awakening LLM Reasoning via Adversarial Learning and Instructive Verbal Evaluation

arXiv:2602.05472v2 Announce Type: replace Abstract: The quest for expert-level reasoning in Large Language Models (LLMs) has been hampered by a persistent extit{reward bottleneck}: traditional reinfor

Any-Dimensional Invariant Universality

arXiv:2605.23156v1 Announce Type: new Abstract: Several machine learning models are defined for inputs of any size, such as graphs with different numbers of nodes and point clouds containing varying n

researcharxiv-cs-lg

BarrierSteer: LLM Safety via Learning Barrier Steering

arXiv:2602.20102v2 Announce Type: replace-cross Abstract: Despite the strong performance of large language models (LLMs) across diverse tasks, their susceptibility to adversarial attacks and unsafe co

Contrastive Distribution Matching for Amortized Sequential Monte Carlo in Discrete Diffusion

arXiv:2605.23346v1 Announce Type: new Abstract: Discrete diffusion models have emerged as powerful frameworks for generating structured categorical data. However, efficiently sampling from reward-tilt

safetyarxiv-cs-lg

DDX-TRACE: A Benchmark for Medical Diagnostic Trajectories in VLMs

model-releasesarxiv-cs-cv

arXiv:2605.23629v1 Announce Type: new Abstract: Medical diagnosis is not a single prediction from a fully specified vignette. It is a sequential workup: clinicians decide what evidence to obtain, revi

Decoupling Spatio-Temporal Adapter for Fine-Grained Badminton Action Localization

model-releasesarxiv-cs-cv

arXiv:2605.23355v1 Announce Type: new Abstract: Temporal Action Localization (TAL) has been extensively studied in generic video understanding, while fine-grained sports scenarios, such as professiona

Enhancing Blood Cells Classification using Hybrid Quantum Neural Networks

arXiv:2605.23324v1 Announce Type: new Abstract: Accurate classification of microscopic blood cells is still a critical task in medical image analysis, where subtle variations and limited data can chal

researcharxiv-cs-cv

Lipschitz Optimization for Formal Verification of Homographies

arXiv:2605.23203v1 Announce Type: cross Abstract: The adoption of vision neural networks in regulated industries requires formal robustness guarantees, especially in safety-critical domains such as he

MedExpMem: Adapting Experience Memory for Differential Diagnosis

arXiv:2605.22872v1 Announce Type: cross Abstract: Experienced physicians develop diagnostic expertise through clinical practice, acquiring not only disease knowledge but also the ability to differenti

Pointwise Metrics Mislead: An Evaluation Protocol for Multimodal Inverse Problems

arXiv:2605.22891v1 Announce Type: new Abstract: Evaluation in scientific reconstruction is dominated by pointwise metrics - RMSE, MAE, per-event resolution - under the implicit assumption that lower e

Reinforcement Learning for Microcanonical Graph Ensemble with Assortativity Constraints

arXiv:2605.23285v1 Announce Type: cross Abstract: How network structure determines function is a fundamental question, and it can be investigated by graph ensembles with precisely controlled structura

Robust LLM Watermarking with Minimal Semantic Distortion for IP Protection

arXiv:2605.23175v1 Announce Type: cross Abstract: Proprietary large language models (LLMs) face risks of intellectual property (IP) violation, as adversaries can replicate an LLM by collecting input-o

researcharxiv-cs-cl

Semantically Structured Mixture-of-Experts for Compositional Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2605.23477v1 Announce Type: new Abstract: Diffusion-based policies have established a new standard for precise robotic manipulation but face a critical scalability bottleneck: high-performance m

SemEval-2026 Task 6: CLARITY -- Unmasking Political Question Evasions

model-releasesarxiv-cs-cl

arXiv:2603.14027v2 Announce Type: replace Abstract: Political speakers often avoid answering questions directly while maintaining the appearance of responsiveness. Despite its importance for public di