Search: “evaluation”

RCAP: Robust, Class-Aware, Probabilistic Dynamic Dataset Pruning

arXiv:2606.11761v1 Announce Type: new Abstract: Dynamic data pruning techniques aim to reduce computational cost while minimizing information loss by periodically selecting representative subsets of i

researcharxiv-cs-lg

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Research

REACH: Interpretability-Driven Feature Identification and Architecture Compression for Multi-Channel Vehicular Channel Estimation

DGX agent

arXiv:2606.11857v1 Announce Type: cross Abstract: Multi-channel mixed-SNR training improves out-of-distribution (OOD) generalisation of deep learning channel estimators for IEEE 802.11p vehicular comm

researcharxiv-cs-lg

11 Jun 2026

Reason, Then Re-reason: Cross-view Revisiting Improves Spatial Reasoning

arXiv:2606.11683v1 Announce Type: cross Abstract: Spatial reasoning from egocentric videos is inherently challenging because the observable evidence is constrained by the camera trajectory. Existing m

researcharxiv-cs-ai

Reinforcement Learning Disrupts Gradient-Based Adversarial Optimization

arXiv:2606.12251v1 Announce Type: cross Abstract: Gradient-based adversarial attacks remain a dominant threat to deep neural networks (DNNs), as they exploit gradient information to efficiently optimi

Resource-Aware LLM Reasoning for Mobile Edge General Intelligence

arXiv:2509.23248v3 Announce Type: replace Abstract: The rapid advancement of large language models (LLMs) has enabled an emergence of agentic artificial intelligence (AI) with powerful reasoning and a

Restless bandits with imperfect binary feedback: PCL-indexability analysis and computation

model-releasesarxiv-cs-lg

arXiv:2606.11192v1 Announce Type: new Abstract: We study restless bandits with binary latent states and imperfect binary feedback, motivated by opportunistic spectrum access with sensing errors. For t

Runtime Skill Audit: Targeted Runtime Probing for Agent Skill Security

arXiv:2606.11671v1 Announce Type: cross Abstract: Agent skills let LLM agents reuse instructions, resources, tools, and workflows, but they also create a new place for malicious behavior to hide. A sk

Seeing Before Colliding: Anticipatory Safe RL with Frozen Vision-Language Models

arXiv:2606.11266v1 Announce Type: new Abstract: The cost signal that constrained-RL algorithms optimize against is almost always reactive: the simulator emits a non-zero cost only after a collision ha

safetyarxiv-cs-lg

Semantically-Aware Diver Activity Recognition Framework for Effective Underwater Multi-Human-Robot Collaboration

arXiv:2606.12374v1 Announce Type: cross Abstract: Effective multi-human-robot collaboration is essential for expanding human-led operations in the challenging and high-risk underwater environment. For

safetyarxiv-cs-cv

SIL: Symbiotic Interactive Learning for Language-Conditioned Human-Agent Co-Adaptation

arXiv:2511.05203v3 Announce Type: replace Abstract: Today's autonomous agents, largely driven by foundation models (FMs), can understand natural language instructions and solve long-horizon tasks with

safetyarxiv-cs-ro

Sovereign Assurance Boundary: Certificate-Bound Admission for Agentic Infrastructure

arXiv:2606.11632v1 Announce Type: cross Abstract: Agentic infrastructure introduces a critical control-plane authorization problem: non-deterministic reasoning systems can propose high-stakes mutation

Space-sampled Value Decay: Forgetting Mechanisms for Non-stationary Deep Reinforcement Learning

arXiv:2606.11797v1 Announce Type: new Abstract: Studies on rodents such as mice have shown the capabilities to adapt their behavior when dealing with changing parameters (``drift'') of the environment

researcharxiv-cs-lg

Sparse probes and murky physics: a case study of interpretability challenges in a foundation model for continuum dynamics

arXiv:2606.11657v1 Announce Type: cross Abstract: Generative AI emulators are increasingly used in scientific domains where we already have strong theory, benchmarks, and physical intuition. This rais

Spectrally Regularized Latent Flow Matching for Turbulence Generation

arXiv:2606.11691v1 Announce Type: new Abstract: Latent diffusion and flow matching have emerged as leading approaches for synthetic turbulence generation, yet they systematically under-represent dissi

safetyarxiv-cs-lg

SR-LIO++: LiDAR-Inertial Odometry and Quantized Mapping with Caching-Aware Sweep Reconstruction

arXiv:2503.22926v3 Announce Type: replace Abstract: Addressing the inherent low acquisition frequency limitation of 3D LiDAR to achieve high-frequency output has become a critical research focus in th

researcharxiv-cs-ro

StatefulDiscovery: Evidence-Calibrated Claim Formation in Open-Ended Scientific Discovery

arXiv:2606.11851v1 Announce Type: new Abstract: Open-ended scientific discovery asks agents to move beyond executing analyses for predefined questions. Across multiple rounds of exploration, a discove

STEAM: Squeeze and Transform Enhanced Attention Module

model-releasesarxiv-cs-cv

arXiv:2412.09023v3 Announce Type: replace Abstract: Channel and spatial attention mechanisms introduced in earlier work enhance the representational capabilities of deep convolutional neural networks

Applications

T2MM: An LLM Supported Architecture For Inquiry-Based Modeling

arXiv:2606.11210v1 Announce Type: cross Abstract: Model Construction is a foundational practice in science learning that relies on visualization and interactivity. Large Language Models, increasingly

applicationsarxiv-cs-ai

Tabular Foundation Models for Clinical Survival Analysis via Survival-Aware Adaptation

arXiv:2606.12006v1 Announce Type: cross Abstract: Predicting time-to-event outcomes such as mortality is a fundamental task in clinical decision-making, commonly addressed through survival analysis. W

researcharxiv-cs-ai

Tac-DINO: Learning Vision-Tactile Features with Patch Alignment

model-releasesarxiv-cs-cv

arXiv:2606.12069v1 Announce Type: new Abstract: Touch is the primary medium through which humans interact with the environment. Currently, tactile learning mainly focuses on image-level pretraining or

TAHOE: Text-to-SQL with Automated Hint Optimization from Experience

arXiv:2606.12387v1 Announce Type: cross Abstract: Large Language Models (LLMs) have democratized database access through Text-to-SQL, but moving from prototypes to production remains difficult. Real d

Task-Aware Structured Memory for Dynamic Multi-modal In-Context Learning

arXiv:2606.11853v1 Announce Type: cross Abstract: Multi-modal large language models (MLLMs) depend on in-context learning (ICL) for rapid task adaptation, but their scalability is severely limited by

Tutorials

TaskFusion: Continual Anomaly Detection for Heterogeneous Tabular Data

arXiv:2606.11844v1 Announce Type: new Abstract: Continual anomaly detection in tabular data is challenging and remains largely underexplored, particularly in settings with heterogeneous feature schema

tutorialsarxiv-cs-lg

Teaching Diffusion to Speculate Left-to-Right

model-releasesarxiv-cs-cl

arXiv:2606.11552v1 Announce Type: new Abstract: Large language models (LLMs) achieve remarkable performance across a wide range of tasks, but their autoregressive decoding process incurs substantial i

Temporal2Seq: A Unified Framework for Temporal Video Understanding Tasks

arXiv:2409.18478v2 Announce Type: replace Abstract: With the development of video understanding, there is a proliferation of tasks for clip-level temporal video analysis, including temporal action det

researcharxiv-cs-cv

Tensor Methods: A Unified and Interpretable Approach for Material Design

arXiv:2602.10392v2 Announce Type: replace Abstract: When designing new materials, it is often necessary to tailor the material design to have some desired properties. As the set of design parameters g

researcharxiv-cs-lg

TextHOI-3D: Text-to-3D Hand-Object Interaction via Discrete Multi-View Generation and Joint Mesh Optimization

arXiv:2606.11805v1 Announce Type: cross Abstract: Text-conditioned 3D generation has progressed rapidly for images and isolated objects, but producing a hand-object mesh remains challenging: the outpu

researcharxiv-cs-ai

The Impossibility of Eliciting Latent Knowledge

arXiv:2606.12268v1 Announce Type: new Abstract: Advanced AI systems have extensive knowledge of their environments; in fact, their knowledge may (far) exceed that of their developers or users. Consequ

The Long Tail, Not the Front Page: Cold-Start Prediction of Crowd Highlight Salience

arXiv:2606.11654v1 Announce Type: cross Abstract: A social highlighter's most useful signal -- which passages a crowd of readers marks -- exists only for documents people have already read. Can the ag

researcharxiv-cs-cl

The N-Body Problem: Parallel Execution from Single-Person Egocentric Video

model-releasesarxiv-cs-cv

arXiv:2512.11393v2 Announce Type: replace Abstract: Humans can intuitively parallelise complex activities, but can a model predict this from observing a single person? Given one egocentric video, we i

The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes

arXiv:2606.11470v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved strong performance across natural language processing tasks, yet reliable reasoning remains an open challenge

agentsarxiv-cs-cl

The Standard Interpretable Model: A general theory of interpretable machine learning to deductively design interpretable methods using Lagrangian mechanics

arXiv:2606.12289v1 Announce Type: cross Abstract: As Artificial Intelligence models grow in complexity, interpretability has become an indispensable tool for understanding, debugging, and controlling

Local Ai

TileFuse: A Fused Mixed-Precision Kernel Library for Efficient Quantized LLM Inference on AMD NPUs

arXiv:2606.11357v1 Announce Type: cross Abstract: With the growing demand for on-device LLM inference, edge SoCs increasingly integrate NPUs to improve performance and energy efficiency under tight po

local-aiarxiv-cs-ai

Time-Conditioned and Multi-Time Survival Prediction from 2D PET/CT Projections in Lung Cancer

arXiv:2606.12140v1 Announce Type: new Abstract: Accurate prediction of overall survival (OS) from positron emission tomography/computed tomography (PET/CT) can support personalized treatment and follo

researcharxiv-cs-cv

Time-Series Foundation Model Embeddings for Remaining Useful Life Estimation

arXiv:2606.11990v1 Announce Type: cross Abstract: Remaining Useful Life (RUL) prediction is essential for industrial predictive maintenance, yet many learning-based approaches rely on extensive featur

To Intervene or Not: Guiding Inference-time Alignment with Probabilistic Model Blending

arXiv:2606.11201v1 Announce Type: cross Abstract: The wide deployment of LLMs has made model alignment necessary to make newly trained models safely and effectively respond to user instructions. Among

Toward Generalist Autonomous Research via Hypothesis-Tree Refinement

arXiv:2606.11926v1 Announce Type: cross Abstract: Scientific progress depends on a repeated loop of exploration, experimentation, and abstraction. Researchers test candidate directions, interpret the

Toward Preference-aligned Large Language Models via Residual-based Model Steering

arXiv:2509.23982v2 Announce Type: replace-cross Abstract: Preference alignment is a critical step in making Large Language Models (LLMs) useful and aligned with (human) preferences. Existing approache

Towards Fully Automated Exam Grading: Fairness-Aware Recognition of Handwritten Answers with Foundation Models

arXiv:2606.11477v1 Announce Type: cross Abstract: Correcting handwritten exams by hand is time-consuming and error-prone, particularly for large cohorts, while fully digital exams tend to force a dida

UniIntervene: Agentic Intervention for Efficient Real-World Reinforcement Learning

arXiv:2606.12372v1 Announce Type: cross Abstract: Human-in-the-loop reinforcement learning (HiL-RL) has emerged as an effective paradigm for real-world robotic manipulation, enabling online policy imp

safetyarxiv-cs-lg

Using Explainability as a Training-Time Reliability Signal for Efficient ECG Classification

arXiv:2606.12252v1 Announce Type: cross Abstract: Training deep neural networks for clinical time-series analysis is computationally demanding, yet many healthcare settings lack the resources required

Vector Quantized Latent Concepts: A Scalable Alternative to Clustering-Based Concept Discovery

arXiv:2602.02726v2 Announce Type: replace-cross Abstract: Large language models (LLMs) encode rich semantic information in their hidden states, yet it remains difficult to understand what information

researcharxiv-cs-cl

VLGA: Vision-Language-Geometry-Action Models for Autonomous Driving

arXiv:2606.12396v1 Announce Type: new Abstract: Vision-language-action (VLA) models can describe scenes and reason about them in language, yet still struggle to ground their actions in the dense 3D wo

safetyarxiv-cs-cv

VOID: Defeating Unauthorized Mimicry in Latent Diffusion Models

arXiv:2606.12263v1 Announce Type: new Abstract: While Latent Diffusion Models (LDMs) have revolutionized visual synthesis, they are increasingly exploited for unauthorized mimicry of individuals. Exis

researcharxiv-cs-cv

When Does Language Matter? Multilingual Instructions Reveal Step-wise Language Sensitivity in Vision-Language-Action Models

model-releasesarxiv-cs-cl

arXiv:2606.11906v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong performance in language-conditioned robotic manipulation, yet their robustness to linguistic varia

Tutorials

When is Your LLM Steerable?

arXiv:2606.11599v1 Announce Type: new Abstract: Activation steering offers a lightweight approach to control language models' behavior at inference time, but whether it succeeds or fails heavily depen

tutorialsarxiv-cs-cl

When More Documents Hurt RAG: Mitigating Vector Search Dilution with Domain-Scoped, Model-Agnostic Retrieval

arXiv:2606.11350v1 Announce Type: new Abstract: Retrieval-augmented generation degrades when scaled to large, heterogeneous document collections, where dense similarity loses discriminative power, and

agentsarxiv-cs-cl

Which Models Are Our Models Built On? Auditing Invisible Dependencies in Modern LLMs

model-releasesarxiv-cs-cl

arXiv:2606.12385v1 Announce Type: new Abstract: Modern LLM training pipelines increasingly rely on other models to generate data, filter corpora, judge outputs, and guide development decisions. These