Search: “evaluation”

MoPET: Parameter-Efficient Mixture-of-Experts for Unified Medical Image Classification

arXiv:2607.29462v1 Announce Type: cross Abstract: Adapting deep learning models to profound clinical heterogeneity typically relies on parameter-efficient fine-tuning (PEFT) to avoid the severe overfi

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Multi-Agent Planning with Spatio-Temporal and Topological Constraints using STL-GO

DGX agent

arXiv:2607.28679v1 Announce Type: new Abstract: Multi-agent planning problems arise in a variety of engineering applications, such as multi-robot wildfire fighting and unmanned aerial inspection in fa

model-releasesarxiv-cs-ai

3 Aug 2026

Local Ai

Multimodal Reinforcement Learning with Adaptive Verifier for AI Agents

arXiv:2512.03438v3 Announce Type: replace Abstract: Agentic reasoning models trained with multimodal reinforcement learning (MMRL) have become increasingly capable, yet they are almost universally opt

local-aiarxiv-cs-ai

NeuroSynth: A Biologically Inspired Continual Reinforcement Learning Architecture for Mitigating Catastrophic Forgetting

arXiv:2607.28663v1 Announce Type: cross Abstract: Artificial Intelligence (AI) systems often perform well on isolated tasks but struggle under continual learning conditions, where training on new task

safetyarxiv-cs-lg

Applications

NeurOWL: An LLM-Based Neural-symbolic Framework for Incomplete OWL Ontology Reasoning

arXiv:2607.15776v2 Announce Type: replace Abstract: OWL ontologies provide a formal knowledge representation framework that enables semantic reasoning, and have been widely adopted across domains such

applicationsarxiv-cs-ai

On the Efficacy of Self-Supervised Point Cloud Encoders for Efficient 3D Large Language Models

arXiv:2607.29136v1 Announce Type: new Abstract: 3D point cloud-language models (3D-LLMs) enable 3D understanding by pairing point cloud encoders with large language models, but existing methods rely o

safetyarxiv-cs-cv

On the Generalization of Steering Vectors for Chain-of-Thought Faithfulness

arXiv:2607.29062v1 Announce Type: new Abstract: Model capabilities have improved in large part due to scaling chain of thought. This has been a promising development for AI safety--where models verbal

OPERA: Online Data Pruning for Efficient Retrieval Model Adaptation

arXiv:2603.17205v3 Announce Type: replace-cross Abstract: Domain-specific finetuning is essential for dense retrievers, yet not all data pairs contribute equally to the learning process. We introduce

researcharxiv-cs-ai

Ordered-to-disordered transfer learning with graph neural networks for formation-energy and HOMO-LUMO gap prediction in high-entropy perovskite oxides

arXiv:2607.29510v1 Announce Type: cross Abstract: High-entropy perovskite oxides (HEPOs) represent a chemically complex class of materials with promising functional properties, yet their vast composit

OSEF: One-Step Evidence Fusion for Cross-Video Scene Procedure Planning

arXiv:2607.29401v1 Announce Type: new Abstract: Video Scene Procedure Planning (VSPP) supplies the target start-goal observations in advance, leaving open how a planner should act when the evidence mu

Outcome-Guided Distillation: A Teacher-Student Framework to Advance VLM Reasoning in Autonomous Driving

arXiv:2607.29052v1 Announce Type: new Abstract: End-to-end (E2E) autonomous driving aims to learn a direct mapping from visual observations to control actions. However, these E2E models often act as b

agentsarxiv-cs-ro

Patch-Based 3D Variational Autoencoder for Super-Resolution of Turbulent Channel Flow

arXiv:2507.22082v2 Announce Type: replace-cross Abstract: Direct numerical simulation (DNS) accurately resolves all spatio-temporal scales of wall-bounded turbulence but becomes prohibitively expensiv

Physics-Aligned Self-Supervised Learning for Scientific Imaging

arXiv:2607.28868v1 Announce Type: new Abstract: Data augmentations define the invariances learned by self-supervised learning (SSL). Standard augmentation pipelines were designed for natural images, y

safetyarxiv-cs-cv

PluRel-to-RDB-PFN: Schema-Guided Synthetic Relational Pretraining

model-releasesarxiv-cs-lg

arXiv:2607.29129v1 Announce Type: new Abstract: Relational Foundation Models (RFMs) require large-scale synthetic relational databases for pretraining, but existing approaches tightly couple data gene

Hardware

Point2Radio: A Foundation Model for Cross-Scene Radio Fields from Material-Aware Point Clouds

arXiv:2607.28994v1 Announce Type: cross Abstract: High-fidelity radio fields are typically simulated for every scene--transmitter configuration or fitted separately to each scene, failing to exploit p

hardwarearxiv-cs-ai

PTP: Previous-Token Prediction based LLM Inversion for Near-Exact Prompt Reconstruction

arXiv:2607.29378v1 Announce Type: new Abstract: Large language models (LLMs) generate text by auto-regressively sampling the next token. This inherently leads to a many-to-many mapping between prompts

Pyramidal Width Can Increase Under Vertex Insertion

arXiv:2607.29555v1 Announce Type: new Abstract: Lacoste-Julien and Jaggi conjectured in 2015 that the pyramidal width of a polytope cannot increase when a vertex is added, provided that every old poin

QASP: Query-Adaptive Robust Vector Search Policy

arXiv:2607.29606v1 Announce Type: cross Abstract: A fundamental challenge of vector search is achieving consistently high recall while minimizing computational costs. Fixed search parameters cause sig

safetyarxiv-cs-lg

QR-Structured Thermal Triggers for Targeted Semantic Attacks on Infrared Vision-Language Models

arXiv:2607.29445v1 Announce Type: cross Abstract: Infrared vision-language models (IR-VLMs) extend thermal perception to open-vocabulary classification, image captioning, and visual question answering

RePaCA: Leveraging Reasoning Large Language Models for Static Automated Patch Correctness Assessment

arXiv:2507.22580v2 Announce Type: replace-cross Abstract: Automated Program Repair (APR) seeks to automatically correct software bugs without requiring human intervention. However, existing tools tend

ResKV: Reconstructing Omitted Attention Contributions for Fixed-Budget KV Cache Compression

arXiv:2607.29591v1 Announce Type: new Abstract: KV cache compression is essential for efficient long-context inference. Existing eviction methods permanently discard unselected tokens and consequently

ReSum: Synergizing LLM Reasoning and Summarization with Reinforcement Learning

arXiv:2606.13316v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is a central technique for improving long-horizon reasoning in Large Language Models (LLMs). H

researcharxiv-cs-ai

Robust Bidirectional Associative Memory via Regularization Inspired by the Subspace Rotation Algorithm

arXiv:2511.11902v2 Announce Type: replace-cross Abstract: Bidirectional Associative Memory (BAM) trained with Bidirectional Backpropagation (B-BP) often suffers from poor robustness and high sensitivi

Rolling With Resistance: Preference-Optimized LLM Counselors Can Trade Goal Persistence for Relational Attunement in Motivational Interviewing

arXiv:2607.28814v1 Announce Type: cross Abstract: In Motivational Interviewing (MI), a client's sustain talk (arguments for the status quo) calls for the counselor to roll with resistance, a move that

RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model

model-releasesarxiv-cs-ro

arXiv:2607.17977v2 Announce Type: replace Abstract: We present RynnBrain 1.1, a family of embodied foundation models spanning 2B, 9B, and 122B-A10B scales. Trained with a unified spatio-temporal and p

SAF-OPD: Stable Advantage Fusion for On-Policy Distillation

arXiv:2607.29209v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) broadcasts a single response-level reward to every token, while on-policy distillation (OPD) sco

Scaffolding Critical Engagement with GenAI: Transforming Ethnic Minority Preparatory Students' Collaborative Discourse in Prompt Engineering Tasks

arXiv:2607.28630v1 Announce Type: cross Abstract: Generative AI (GenAI) holds significant promise for advancing educational equity among ethnic minority students by broadening access to learning resou

Scaling Scientific Discovery Environments for Turn-Level Agentic RL

arXiv:2607.28990v1 Announce Type: new Abstract: Large language model agents have shown promising capabilities in data-driven scientific discovery tasks, where an agent interacts with an execution envi

agentsarxiv-cs-ai

SciToolAgent-Evo: An Ontology-Aware Self-Evolving Agent for Open-World Scientific Tool Acquisition

arXiv:2607.28692v1 Announce Type: new Abstract: Large language model (LLM) agents have been increasingly adopted in scientific research for organizing and invoking specialized computational tools. How

SEDR-Seq2P: A Lightweight Dilated Residual Sequence-to-Point Network for Multi-Task Industrial NILM

arXiv:2607.28693v1 Announce Type: cross Abstract: Industrial NILM remains challenging because measurement noise and widespread concurrent machine operation reduce the generalization of models tuned on

SeekBrain: An Autonomous Multi-Agent System for Accelerating Neuroscience Discovery

arXiv:2607.29347v1 Announce Type: cross Abstract: Modern neuroscience relies on integrating multi-scale, multimodal datasets to uncover the neural principles underlying intelligence. However, analytic

Self-Supervised Skill Optimization

arXiv:2607.28777v1 Announce Type: new Abstract: Agent skills provide frozen large language model (LLM) agents with reusable procedural guidance, and recent work shows that such skills can be optimized

agentsarxiv-cs-cl

Applications

Semantics of Subterfuge: Benchmarking Legal Deception Detection Against General-domain State-of-the-Art

arXiv:2607.29066v1 Announce Type: cross Abstract: Deception detection has critical implications for legal proceedings, law enforcement, and online security. Although human judgment is limited in accur

applicationsarxiv-cs-ai

SERUM: State Extraction and Refinement for User Modeling

arXiv:2607.29181v1 Announce Type: cross Abstract: Agentic assistants capable of proactive, personalized interactions require structured models of user intent and workflow. However, building these mode

agentsarxiv-cs-ai

Shapley-Value-Based Feature Attribution for Data Masking

arXiv:2607.28946v1 Announce Type: new Abstract: Despite its many benefits, widespread access to individuals' personal data also causes severe privacy concerns for consumers, companies, and policymaker

Side-Channel Attacks Survive Noise Cancellation in 3D Printers

arXiv:2606.13952v2 Announce Type: replace-cross Abstract: Active Motor Noise Cancellation (AMNC) is a noise-reduction feature shipped in commercial fused deposition modeling (FDM) 3D printers. Because

Simple-regret rates and minimax optimality of fixed-prior expected improvement in Matern and squared-exponential RKHSs

arXiv:2607.29245v1 Announce Type: cross Abstract: We study the expected improvement (EI) policy for minimizing a deterministic objective function f on a nonempty compact set mathcal X subsetmathbb R^d

safetyarxiv-cs-lg

Simulative Anomaly Detection using 2D Tomography

arXiv:2607.28701v1 Announce Type: cross Abstract: We present a novel technique for predicting the imaging quality of anomalies such as cancer cells located inside organic tissues. This technique is us

researcharxiv-cs-cv

Stem: Rethinking Causal Information Flow in Sparse Attention

arXiv:2603.06274v2 Announce Type: replace-cross Abstract: The quadratic computational complexity of self-attention remains a fundamental bottleneck for scaling Large Language Models (LLMs) to long con

researcharxiv-cs-ai

Structured Neural Chaos: An Adaptive Surrogate Modeling Framework for Functional Uncertainty Quantification and Global Sensitivity Analysis

arXiv:2607.28903v1 Announce Type: cross Abstract: Variance-based global sensitivity analysis (GSA) plays a key role in uncertainty quantification by identifying the contributions of uncertain inputs t

SULAND v2: A Refined RGB Dataset and Deep Learning Object Detection Benchmark for UAV/UGV-Based SUrface LANDmine Detection Under Domain Shift

arXiv:2607.28996v1 Announce Type: new Abstract: RGB imagery offers a practical, low-cost option for Unmanned Aerial/Ground Vehicle (UAV/UGV) survey support in surface-landmine detection, but object de

Local Ai

TacPrint: A Wearable Fingertip Tactile Sensor for Human-to-Robot Contact Reproduction

arXiv:2607.29231v1 Announce Type: new Abstract: Human-centric data collection is emerging as a significant paradigm for robot skill acquisition, but seamlessly integrating low-cost, scalable tactile s

local-aiarxiv-cs-ro

Teaching Video Generators to Remember: Eliciting Dynamic Memory for Out-of-Sight State Evolution

arXiv:2605.25333v2 Announce Type: replace Abstract: Video world models should maintain evolving states when evidence is unobserved, yet current generators often freeze hidden states upon interruption.

TELLER: Dual-Path Iterative Preference Optimization for Table Entity Linking

arXiv:2607.28680v1 Announce Type: new Abstract: Entity linking in tables matches short and ambiguous cell mentions to their corresponding knowledge-base entities. Existing approaches typically rely on

safetyarxiv-cs-cl

The Theoretical Foundation of Socratic Tests: Dynamic, Multimodal, Conversational Examinations

arXiv:2607.29624v1 Announce Type: cross Abstract: Traditional static assessments rely on a subtractive, deficit-based grading model that often penalizes ambition and obscures diagnostic feedback. Conv

Token-Level Diagnosis of Sycophancy in LLMs with Attribution-Guided Steering

arXiv:2607.28906v1 Announce Type: new Abstract: Sycophancy refers to the tendency for large language models (LLMs) to match user beliefs at the cost of factual correctness, thereby undermining model r

Tokenizer Transplantation: Mitigating Autoregressive Collapse in Edge-Efficient Bengali ASR

arXiv:2607.09598v2 Announce Type: replace Abstract: Lightweight speech recognition models are critical for edge deployment, yet highly optimized architectures like Moonshine often fail on morphologica

Hardware

Topology-Aware Data Movement for Disaggregated GPU Inference

arXiv:2607.28633v1 Announce Type: cross Abstract: Disaggregated LLM inference creates a datacenter networking problem that no existing system solves correctly. When prefill and decode run on separate

hardwarearxiv-cs-ai