Search: “evaluation”

Comparing the Performance of Foundation Model Derived Embeddings with Traditional Approaches for Distant Metastasis Prediction in Head and Neck Cancer

arXiv:2607.26276v1 Announce Type: new Abstract: Background: Early prediction of distant metastasis (DM) risk in head and neck cancer (HNC) can enable timely interventions that may improve treatment ou

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Constitutional Midtraining: Content Presence Drives Alignment Gains

DGX agent

arXiv:2607.26654v1 Announce Type: new Abstract: Post-training alignment is often shallow, eroding under fine-tuning. Whether midtraining interventions, cleanly isolated from post-training, can produce

safetyarxiv-cs-cl

30 Jul 2026

Context-measure: Contextualizing Metric for Camouflage

arXiv:2512.07076v4 Announce Type: replace Abstract: Camouflage relies heavily on context, but current metrics used in camouflaged object segmentation ignore contextual cues. We identify two major draw

Controlled Experiments on Lane Changing by Transitional Autonomous Vehicle: Dataset and Behavioral Insights

arXiv:2607.27085v1 Announce Type: new Abstract: This paper presents the North Carolina Transitional Autonomous Vehicle Lane-Changing (NC-tALC) dataset and uses it to characterize mandatory lane-changi

safetyarxiv-cs-ro

Crossing-Free Probabilistic K-Line Forecasts Without Retraining

arXiv:2607.26792v1 Announce Type: cross Abstract: Probabilistic K-line forecasting describes uncertainty in four complementary prices, namely open--high--low--close (OHLC). However, it introduces two

Data Fusion and Contrastive Alignment for Unconstrained IR Molecular Structure Elucidation

arXiv:2607.26164v1 Announce Type: new Abstract: Automated molecular structure elucidation from infrared (IR) spectroscopy data has seen significant advancements in recent years, but its broad applicab

safetyarxiv-cs-lg

Defending Against Backdoor Attacks via Alignment Checking in Model-Contrastive Federated Learning

arXiv:2607.26933v1 Announce Type: cross Abstract: Federated Learning (FL) is vulnerable to backdoor attacks because of its distributed nature in edge computing scenarios. Existing defense methods show

Dice Loss for Data-imbalanced NLP Tasks

arXiv:1911.02855v5 Announce Type: replace Abstract: Many NLP tasks such as tagging and machine reading comprehension are faced with the severe data imbalance issue: negative examples significantly out

researcharxiv-cs-cl

Differentially Private Permutation Tests

arXiv:2310.19043v3 Announce Type: replace-cross Abstract: Recent years have witnessed growing concerns about the privacy of sensitive data. In response to these concerns, differential privacy has emer

applicationsarxiv-cs-lg

DistillAlign: Coordinating Mode Covering and Mode Seeking in Autoregressive Video Distillation

arXiv:2607.26811v1 Announce Type: new Abstract: Existing autoregressive video distillation methods commonly adopt a Distribution Matching Distillation (DMD)-based multi-stage pipeline. However, they t

Early Verdicts, Better Budgets: Sequential Adaptive Rollout Allocation for Compute-Efficient RLVR

arXiv:2607.26253v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) is bottlenecked by rollout generation, yet many sampled prompts produce saturated groups (all resp

safetyarxiv-cs-lg

Eddeep: a deep-learning framework for fast eddy-current distortion correction in diffusion MRI

arXiv:2607.26292v1 Announce Type: new Abstract: Diffusion MRI (dMRI) relies on diffusion-weighted echo-planar imaging, which is highly susceptible to eddy-current-induced geometric distortions. These

Efficient Heteroscedastic Bayesian Optimization for Risk-Aware AutoRL

arXiv:2607.26680v1 Announce Type: new Abstract: Reinforcement learning (RL) has shown remarkable success across a wide range of complex tasks. However, RL outcomes can be highly stochastic, and both e

researcharxiv-cs-lg

Embodied Agents Take Control: Minimal-Interface Zero-Shot Agents Rival Industrial-Scale Policies in Vision-and-Language Navigation

arXiv:2607.26148v1 Announce Type: new Abstract: Autonomous embodied agents must sustain a long decision-making loop that involves perceiving, acting, verifying, and self-correcting over many steps. Cu

agentsarxiv-cs-ro

EvoPINN: Agentic Discovery of Executable Algorithms for Physics-Informed Neural Networks

arXiv:2607.26490v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful paradigm for solving partial differential equations (PDEs), yet their performance

Explainable and Resource-Efficient Spatial Reasoning in Multimodal LLMs for Decision-Critical Applications

arXiv:2607.27145v1 Announce Type: new Abstract: As Multimodal Large Language Models (MLLMs) are increasingly deployed in decision-critical pipelines such as robotics, embodied AI, and safety monitorin

exttt{AMEND++}: Benchmarking Eligibility Criteria Amendments in Clinical Trials

arXiv:2601.06300v2 Announce Type: replace Abstract: Clinical trial amendments frequently introduce delays, increased costs, and administrative burden, with eligibility criteria being the most commonly

FakeIDet3-DB: Refining Digital Attacks and Patch Extraction for Secure ID Benchmarking

arXiv:2607.26641v1 Announce Type: new Abstract: Identity document (ID) authentication relies on the structural integrity of complex, high-frequency security patterns. However, advanced Generative AI m

local-aiarxiv-cs-cv

Financial Volatility and Risk Forecasting Incorporating a Larger Number of Realized Measures

arXiv:2411.17136v2 Announce Type: replace-cross Abstract: Realised volatility has become increasingly prominent in volatility forecasting due to its ability to capture intraday price fluctuations. Wit

From Classification to Regression: Using a Fruitfly to Solve Equations

arXiv:2607.27196v1 Announce Type: new Abstract: We present a novel approach to regression tasks using classification which is motivated by the mechanism used by fruitflies to sense their environment.

local-aiarxiv-cs-lg

From Keypoints to Predictive Distributions: Post-Hoc Uncertainty for YOLO-Pose Models

arXiv:2607.26921v1 Announce Type: new Abstract: YOLO-Pose models provide efficient keypoint localization, but do not quantify the associated spatial uncertainty. We introduce a lightweight post-hoc pr

local-aiarxiv-cs-cv

Tutorials

From Passive Video to Editable Experience: Physically Grounded Experience Synthesis for Embodied Intelligence

arXiv:2607.26903v1 Announce Type: cross Abstract: The key bottleneck in embodied AI is not model architecture but data. Although billions of human manipulation videos exist online, robots cannot direc

tutorialsarxiv-cs-ro

From Tokens to Watt-hours: Analytical Energy Estimation for LLM Inference on Modern GPUs

arXiv:2607.26571v1 Announce Type: new Abstract: The operational energy consumption of large language model (LLM) inference is becoming an increasingly important component of the environmental footprin

GPT-Red: Automated Red Teaming via Self-Play at Scale

arXiv:2607.26115v1 Announce Type: cross Abstract: We introduce extbf{GPT-Red}, an automated red-teaming agent that is trained to discover novel prompt injection attacks against frontier LLMs. The goal

Hearsay: Vision-Language Medical Diagnoses Without an Image

arXiv:2607.26886v1 Announce Type: cross Abstract: When asked to describe a medical image that was never attached, frontier vision-language models do not abstain: they confabulate a diagnosis. We show

Heterogeneous Element-Aware Cross-Version Differencing of Scientific Documents via Layout-Aware Alignment and Structure-Aware Reasoning

arXiv:2607.14117v2 Announce Type: replace Abstract: Cross-version differencing of scientific documents is essential in scholarly publishing and technical documentation, but remains challenging because

safetyarxiv-cs-cl

InkShield: Writing Style Protection Against Unauthorized Handwriting Mimicry

arXiv:2607.26976v1 Announce Type: cross Abstract: Recent handwritten text generators can reproduce a writer's style from publicly available references, posing risks of document forgery and identity mi

Inverse Learning of Latent Risk-Neutral Densities from Irregular Option Quotes

arXiv:2607.27188v1 Announce Type: new Abstract: Accurate option prices do not imply accurate recovery of the latent risk-neutral density. We study this distinction with two complementary benchmarks. A

JEPADepth: Masked Predictive Representation Learning for Self-Supervised Monocular Depth Estimation

model-releasesarxiv-cs-cv

arXiv:2607.26600v1 Announce Type: new Abstract: Self-supervised monocular depth estimation typically relies on photometric reconstruction losses that couple depth, pose, and appearance assumptions. In

Kairos: Numerically Robust News Recommendation under Item Cold-Start via Cholesky-based LinUCB

arXiv:2607.26832v1 Announce Type: new Abstract: Algorithmic news personalization in regional markets often fails because modern deep learning models require massive interaction data while real-world n

applicationsarxiv-cs-lg

Keyless Attention: Value-Space Routing and Value-Only Caching for Efficient Transformers

arXiv:2606.21848v2 Announce Type: replace Abstract: Transformer architectures form the foundation of modern natural language processing, making it crucial to address the efficiency and scalability lim

researcharxiv-cs-cl

Knowledge before Reasoning: EC-Reason-Bench, a Training-Free Diagnostic Benchmark for LLM Enzyme Classification

arXiv:2607.26397v1 Announce Type: new Abstract: Enzyme function prediction is a hierarchical, knowledge-intensive form of protein function classification. Existing benchmarks expose an anomaly: genera

LAMUS: A Large-Scale Corpus for Legal Argument Mining from U.S. Caselaw using LLMs

arXiv:2603.08286v2 Announce Type: replace Abstract: Legal argument mining aims to identify and classify the functional components of judicial reasoning, such as facts, issues, rules, analysis, and con

applicationsarxiv-cs-cl

Language Models are not Equally Robust to Non-Canonical Tokenization across Languages

arXiv:2607.26831v1 Announce Type: new Abstract: Despite the existence of exponentially many valid tokenizations for a given string, language models operate on a single canonical sequence deterministic

Learning Implicit Causal World Models from Multi-Agent Demonstrations

arXiv:2607.26336v1 Announce Type: new Abstract: In model-based reinforcement learning, world models exist as internal simulators, but their training often conflates statistical correlations with causa

safetyarxiv-cs-lg

Living-Harness Is an Interactive-Agent Evolver

arXiv:2607.26598v1 Announce Type: cross Abstract: Large language model (LLM) agents may recover from a failure within an episode or after a retry, yet the same execution failure can recur in later tas

agentsarxiv-cs-cl

Making Implicit Premises Explicit in Logical Understanding of Enthymemes

arXiv:2603.06114v2 Announce Type: replace Abstract: Real-world arguments in text and dialogues are normally enthymemes (i.e. some of their premises and/or claims are implicit). Natural language proces

applicationsarxiv-cs-cl

MediaWiki Code2Code Search: Neural Retrieval for the Semantic Discovery of Open-Source Software Entities

arXiv:2607.26766v1 Announce Type: cross Abstract: Code search in large-scale ecosystems is often hindered by the lexical gap between user queries and implementation details, alongside the trade-off be

MetaKoopman: Bayesian Meta-Learning of Koopman Operators for Modeling Structured Dynamics under Distribution Shifts

arXiv:2607.26345v1 Announce Type: new Abstract: Modeling and forecasting nonlinear dynamics under distribution shifts is essential for robust decision-making in real-world systems. In this work, we pr

agentsarxiv-cs-lg

MindForge: Teaching Small Language Models Whole-Life-Cycle Software Engineering via Source-Free Program Synthesis

arXiv:2607.27146v1 Announce Type: cross Abstract: Coding agents have made substantial progress on software engineering tasks that modify existing codebases, including bug fixing and feature implementa

agentsarxiv-cs-cl

MoSAIC: Aligned Intervention Supervision for Part-Local Motion Style Transfer

arXiv:2607.26304v1 Announce Type: new Abstract: Editing character motion often requires transferring a gesture or gait from one or more reference motions while preserving the source action, timing, ro

local-aiarxiv-cs-cv

No Data Is Not No Risk: Visibility Aware Graph-Based Inference of Business Conduct Risk

arXiv:2607.26859v1 Announce Type: cross Abstract: The monitoring of business conduct risk is hindered by sparse, uneven, and visibility-biased data. Prior studies show that business conduct risk infor

researcharxiv-cs-lg

Online Handwriting Trajectory Reconstruction from Kinematic Sensors using Temporal Convolutional Network

model-releasesarxiv-cs-cv

arXiv:2607.26733v1 Announce Type: new Abstract: Handwriting with digital pens is a common way to facilitate human-computer interaction through the use of Online Handwriting (OH) trajectory reconstruct

Physics-Informed Graph Neural Networks for Robust AC-Optimal Power Flow

arXiv:2410.04818v2 Announce Type: replace-cross Abstract: We present PINCO, an unsupervised learning framework that integrates Graph Neural Networks with physics-informed neural networks for AC optima

researcharxiv-cs-lg

R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning

arXiv:2607.26583v1 Announce Type: new Abstract: Point-cloud (PC) registration is fundamental to three-dimensional (3D) perception in robotic systems. However, classic registration algorithms falter wh

RA-Det: Towards Universal Detection of AI-Generated Images via Robustness Asymmetry

arXiv:2603.01544v2 Announce Type: replace Abstract: Recent image generators produce photo-realistic content that undermines the reliability of downstream recognition systems. As visual appearance cues

RAGuard: A Layered Defense Framework for Retrieval-Augmented Generation Systems Against Data Poisoning

arXiv:2607.26339v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems ground large language models (LLMs) in external corpora, but this reliance exposes them to corpus poisoning

Reeling It In: Flexible Needle Pick Up via Thread Manipulation for Autonomous Suturing

model-releasesarxiv-cs-ro

arXiv:2607.26337v1 Announce Type: new Abstract: Suture-needle pickup is necessary for autonomous suturing, as a needle can be unexpectedly dropped or strategically released to adjust the grasping conf