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Towards a Bridge Layer Between Bibliographic and Formalized Mathematical Knowledge

arXiv:2606.11430v1 Announce Type: cross Abstract: Mathematical knowledge is split between bibliographic databases (e.g., MathSciNet, zbMATH Open) and formal proof libraries (e.g., Lean mathlib), preve

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Towards Conditional Feature Alignment for Cross-Domain Counting

DGX agent

arXiv:2506.17137v3 Announce Type: replace Abstract: Object counting models often degrade under cross-domain deployment because density composition varies across domains and is itself task-relevant. St

safetyarxiv-cs-cv

11 Jun 2026

Towards Data-free and Training-free Compression for Speech Foundation Models Using Parameter Clustering

arXiv:2606.11836v1 Announce Type: cross Abstract: This paper presents a novel data-free and training-free compression approach for speech foundation models using channelwise clustering via k-means. Mo

Towards Deep Learning Surrogate for the Forward Problem in Electrocardiology: A Scalable Alternative to Physics-Based Models

arXiv:2512.13765v2 Announce Type: replace-cross Abstract: The forward problem in electrocardiology, computing body surface potentials from cardiac electrical activity, is traditionally solved using ph

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

Agents

Towards Responsibly Non-Compliant Machines

arXiv:2606.12147v1 Announce Type: new Abstract: We consider the problem of engineering autonomous intelligent agents that are capable to responsibly not comply with user requests. We argue that machin

agentsarxiv-cs-ai

Traceable Virtual Sea Trials in the Marine Robotics Unity Simulator for Manoeuvring Assessment of Unmanned Surface Vehicles

arXiv:2606.12349v1 Announce Type: new Abstract: Accurate identification of hydrodynamic derivatives is essential for control and navigation of Unmanned Surface Vehicles (USVs), but high-fidelity manoe

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Traits Run Deeper: Trait-Specific Asymmetric Fusion for Personality Assessment

arXiv:2606.11269v1 Announce Type: new Abstract: Personality assessment aims to infer stable personality traits from dynamic behaviors across language, voice, and facial cues. Since different personali

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Local Ai

Tree-Structured Orthonormal Decomposition of the Aitchison Simplex

arXiv:2606.11646v1 Announce Type: new Abstract: Compositional data -- vectors encoding relative proportions -- arise across scientific domains, including ecology, geochemistry, and genomics. The featu

local-aiarxiv-cs-lg

Agents

TreeSeeker: Tree-Structured Trial, Error, and Return in Deep Search

arXiv:2606.11662v1 Announce Type: new Abstract: Deep search requires agents to answer complex questions through multi-step web search, browsing, evidence comparison, and synthesis. A central challenge

agentsarxiv-cs-ai

Applications

TRON: Tracing Rays to Orchestrate a Neural Renderer for 3D Gaussian Reconstructions

arXiv:2606.11314v1 Announce Type: new Abstract: We introduce TRON, a rendering framework that combines 3D Gaussian ray tracing with neural rendering to enable realistic and controllable rendering of r

applicationsarxiv-cs-cv

UGV-Conditioned Multi-UAV Informative Planning on a Shared Exposure Belief

arXiv:2606.12306v1 Announce Type: new Abstract: Safe ground navigation in large, threat-augmented environments requires aerial support that actively reduces the risks that a ground vehicle faces along

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Understanding Cross-Sensor Feature Variations for Generalizable 3D Perception

arXiv:2606.11573v1 Announce Type: new Abstract: Radar-camera BEV perception often suffers from degraded performance when evaluated across datasets, as changes in driving scenes, sensor configurations,

researcharxiv-cs-cv

Applications

Unifying Learning Dynamics and Generalization in Transformers Scaling Law

arXiv:2512.22088v3 Announce Type: replace-cross Abstract: The scaling law, a cornerstone of Large Language Model (LLM) development, predicts improvements in model performance with increasing computati

applicationsarxiv-cs-ai

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

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UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA

arXiv:2606.11740v1 Announce Type: cross Abstract: We study whether grounded reasoning supervision from abundant 2D medical images can improve 3D medical VQA when both input types are aligned through a

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Unstable Features, Reproducible Subspaces: Understanding Seed Dependence in Sparse Autoencoders

arXiv:2606.12138v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) are widely used to interpret neural network representations, but their utility depends on whether the learned features are

UR-BERT: Scaling Text Encoders for Massively Multilingual TTS Through Universal Romanization and Speech Token Prediction

arXiv:2606.11681v1 Announce Type: new Abstract: We propose UR-BERT, a Romanized transcription-based text-to-speech (TTS) encoder for massively multilingual TTS systems. Conventional grapheme-to-phonem

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Urban Heat MiniCubes: An AI-Ready dataset for urban heat research

arXiv:2606.11534v1 Announce Type: cross Abstract: Urban heat is amplified by impermeable surfaces and heterogeneous built environments, yet street-level variability remains difficult to quantify becau

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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

Applications

uva-irlab-conv at SemEval-2026 Task 8: Multi-Turn RAG with Learned Sparse Retrieval and Listwise Reranking

arXiv:2606.11945v1 Announce Type: new Abstract: This report describes our participation in SemEval-2026 Task 8 on multi-turn retrieval and question answering. The task evaluates conversational systems

applicationsarxiv-cs-cl

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

Verifiable Environments Are LEGO Bricks: Recursive Composition for Reasoning Generalization

arXiv:2606.12373v1 Announce Type: new Abstract: Reinforcement Learning (RL) with verifiable environments has emerged as a powerful approach for enhancing the reasoning capabilities of Large Language M

VIA-SD: Verification via Intra-Model Routing for Speculative Decoding

arXiv:2606.12243v1 Announce Type: cross Abstract: Speculative decoding (SD) addresses the high inference costs of LLMs by having lightweight drafters generate candidates for large verifiers to validat

VICX: Generalizable Robot Manipulation via Video Generation and In-Context Operator Network

model-releasesarxiv-cs-ro

arXiv:2606.12028v1 Announce Type: new Abstract: Generalizable robot manipulation requires not only task-level reasoning over unseen scenes, but also reliable grounding of visual plans into embodiment-

VietMed-MCQ: A Consistency-Filtered Data Synthesis Framework for Vietnamese Traditional Medicine Evaluation

arXiv:2601.03792v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable proficiency in general medical domains. However, their performance significantly degrades

Vision-Aided Relative State Estimation for Approach and Landing on a Moving Platform with Inertial Measurements

arXiv:2512.19245v2 Announce Type: replace-cross Abstract: This paper tackles the problem of estimating the relative position, orientation, and velocity between a UAV and a planar platform undergoing a

researcharxiv-cs-ro

Vision Transformers for Face Recognition Need More Registers

arXiv:2606.12036v1 Announce Type: new Abstract: Recent advances in Vision Transformers (ViTs) for face recognition (FR) have moved beyond the standard CLS-token paradigm. In this paradigm, a special c

researcharxiv-cs-cv

Visualizing LLM Latent Space Geometry Through Dimensionality Reduction

model-releasesarxiv-cs-lg

arXiv:2511.21594v3 Announce Type: replace Abstract: Large language models (LLMs) achieve state-of-the-art results across many natural language tasks, but their internal mechanisms remain difficult to

ViT-FREE: Efficient Face Recognition via Early Exiting and Synthetic Adaptation

arXiv:2606.12023v1 Announce Type: new Abstract: Vision Transformers (ViTs) have gained significant attention in computer vision and shown strong potential for face recognition (FR). However, their hig

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VL-DINO: Leveraging CLIP Vision-Language Knowledge for Open-Vocabulary Object Detectio

model-releasesarxiv-cs-cv

arXiv:2606.11546v1 Announce Type: new Abstract: Vision-language models like CLIP can provide rich semantic priors for open-vocabulary object detection. However, jointly integrating both textual and vi

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

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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

Weighted Random Dot Product Graphs

arXiv:2505.03649v4 Announce Type: replace-cross Abstract: Modeling of intricate relational patterns has become a cornerstone of contemporary statistical research and related data science fields. Netwo

researcharxiv-cs-lg

What Limits Does Quantization Place on Dense Top-k Retrieval? A Theoretical Study

arXiv:2606.11780v1 Announce Type: cross Abstract: We establish conditions for embedding a corpus of N documents as d-dimensional vectors such that every k-subset S subseteq [N] is realizable as a resu

What Uncertainties Do We Need for Dynamical Systems?

arXiv:2606.11988v1 Announce Type: new Abstract: The distinction between aleatoric and epistemic uncertainty has received considerable attention in machine learning research, mainly in the context of s

researcharxiv-cs-lg

When Context Returns: Toward Robust Internalization in On-Policy Distillation

arXiv:2606.11627v1 Announce Type: cross Abstract: Recent work has shown that on-policy distillation can internalize privileged context, such as system prompts or task hints, into a student model so th

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When Do Data-Driven Systems Exhibit the Capability to Infer?

arXiv:2606.11769v1 Announce Type: new Abstract: The European AI Act is the first comprehensive regulation of artificial intelligence (AI), setting out extensive obligations, particularly for so-called

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

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

When Generic Prompt Improvements Hurt: Evaluation-Driven Iteration for LLM Applications

arXiv:2601.22025v2 Announce Type: replace-cross Abstract: Evaluating Large Language Model (LLM) applications differs from conventional software testing because outputs are probabilistic, semantically

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

Agents

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

When Poison Fails After Retrieval: Revisiting Corpus Poisoning under Chunking and Reranking Pipelines

arXiv:2606.11265v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are vulnerable to corpus poisoning attacks that manipulate downstream model outputs through malicious kno

When Probing Accuracy Saturates, Fragility Resolves: A Complementary Metric for LLM Pre-Training Analysis

arXiv:2606.11375v1 Announce Type: cross Abstract: Standard linear probing declares a property 'encoded' when a classifier on hidden states achieves high accuracy. The protocol works well on a snapshot

When Researchers Say Mental Model/Theory of Mind of AI, What Are They Really Talking About?

arXiv:2510.02660v2 Announce Type: replace-cross Abstract: When researchers claim AI systems possess ToM or mental models, they are fundamentally discussing behavioral predictions and bias corrections

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When Roleplaying, Do Models Believe What They Say?

arXiv:2606.11502v1 Announce Type: cross Abstract: Language models can state that 'the Earth orbits the Sun' and, when role-playing Aristotle, assert the opposite. Recent work argues that persona adopt

Where Do Backdoors Live? A Component-Level Analysis of Backdoor Propagation in Speech Language Models

arXiv:2510.01157v4 Announce Type: replace Abstract: Speech language models (SLMs) are systems of systems: independent components that unite to achieve a common goal. Despite their heterogeneous nature

researcharxiv-cs-cl

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

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