Search: “papers”

Constituency Structure over Eojeol in Korean Treebanks

arXiv:2512.22487v2 Announce Type: replace Abstract: The design of Korean constituency treebanks raises a central representational question concerning the choice of terminal units. Although Korean word

safetyarxiv-cs-cl

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Constraint Tax in Open-Weight LLMs: An Empirical Study of Tool Calling Suppression Under Structured Output Constraints

DGX agent

arXiv:2606.25605v1 Announce Type: new Abstract: Tool Calling and Structured Output are two core capabilities of modern Agent systems, yet their interaction under joint deployment conditions remains in

model-releasesarxiv-cs-cl

25 Jun 2026

CrossAccent-TTS: Cross-Lingual Accent-Intensity Controllable Text-to-Speech via Disentangled Speaker and Accent Representations

arXiv:2606.25403v1 Announce Type: cross Abstract: Accent conversion and controllability remain fundamental challenges in cross-lingual text-to-speech (TTS), particularly for low-resource and phonetica

researcharxiv-cs-ai

Data-Driven Evolution of Library and Information Science Research Methods (1990-2022): A Perspective Based on Fine-grained Method Entities

arXiv:2606.25320v1 Announce Type: cross Abstract: Since the 1990s, advancements in big data and information technology have increasingly driven data-centric research in the field of Library and Inform

Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning

arXiv:2510.04773v2 Announce Type: replace Abstract: As Large Language Models (LLMs) demonstrate remarkable capabilities learned from vast corpora, concerns regarding data privacy and safety are receiv

Do Encoders Suffice? A Systematic Comparison of Encoder and Decoder Safety Judges for LLM Adversarial Evaluation

model-releasesarxiv-cs-cl

arXiv:2606.25782v1 Announce Type: new Abstract: With the widespread adoption of large language models (LLMs) in chatbots and everyday applications, companies increasingly need guardrails that are effe

Dziri Voicebot: An End-to-End Low-Resource Speech-to-Speech Conversational System for Algerian Dialect

arXiv:2606.26003v1 Announce Type: new Abstract: Automatic speech and language technologies are still heavily biased toward high-resource languages, limiting their applicability to dialectal and low-re

Efficient Remote Sensing Instance Segmentation with Linear-Time State Space Distilled Visual Foundation Models

model-releasesarxiv-cs-cv

arXiv:2606.25324v1 Announce Type: new Abstract: The computational complexity of Transformers scales quadratically with the number of tokens, which significantly constrains the efficiency of vision mod

Emergent Capabilities Arise Randomly from Learning Sparse Attention Patterns

arXiv:2606.25010v1 Announce Type: cross Abstract: Neural scaling laws for transformer language models predict smooth improvements in pretraining loss with increasing parameters, but downstream capabil

End-to-End Voice Intent Recognition for Spontaneous Human-Drone Interaction with Naive Users

arXiv:2606.24910v1 Announce Type: cross Abstract: Voice control offers an intuitive alternative to manual drone piloting, yet most existing systems rely on rigid command vocabularies that fail to hand

researcharxiv-cs-ai

Epistemic Bias Injection: Manipulating LLM Opinion via Selective Context Retrieval

model-releasesarxiv-cs-ai

arXiv:2512.00804v3 Announce Type: replace-cross Abstract: When answering user queries, LLMs often retrieve knowledge from external sources stored in retrieval-augmented generation (RAG) databases. The

Local Ai

Explainable Control Framework (XCF) based on Fuzzy Model-Agnostic Explanation and LLM Agent-Supported Interface

arXiv:2606.25941v1 Announce Type: cross Abstract: Increasing demand for precise and reliable control in complex scenarios has led to the development of increasingly sophisticated controllers, includin

local-aiarxiv-cs-ai

Extreme Meta-Classification for Large-Scale Zero-Shot Retrieval

arXiv:2606.25237v1 Announce Type: cross Abstract: We develop accurate and efficient solutions for large-scale retrieval tasks where novel (zero-shot) items can arrive continuously at a rapid pace. Con

researcharxiv-cs-lg

Failure Modes of Large Language Models on Research-Level Mathematics: A Taxonomy and an Empirical Characterisation

model-releasesarxiv-cs-ai

arXiv:2606.24902v1 Announce Type: cross Abstract: The 'First Proof' benchmark [1] posed ten research-level mathematics questions to the strongest publicly available LLMs and found them consistently wr

FAR-LIO: Enabling High-Speed Autonomy through Fast, Accurate, and Robust LiDAR-Inertial Odometry

model-releasesarxiv-cs-ro

arXiv:2606.26010v1 Announce Type: new Abstract: Robust and accurate odometry estimation is essential in modern robotics. In environments characterized by highly dynamic motion and sensor noise, odomet

Local Ai

FedReLa: Imbalanced Federated Learning via Re-Labeling

arXiv:2606.26037v1 Announce Type: cross Abstract: Federated learning has emerged as the foremost approach for decentralized model training with privacy preservation. The global class imbalance and cro

local-aiarxiv-cs-cv

ForceBand: Learning Forceful Manipulation with sEMG

arXiv:2606.26093v1 Announce Type: new Abstract: Human demonstrations are a scalable data source for learning robot manipulation policies. However, common sources of human demonstration data, such as m

safetyarxiv-cs-ro

Fourier Multi-Component and Multi-Layer Neural Networks: Unlocking High-Frequency Potential

arXiv:2502.18959v4 Announce Type: replace Abstract: The architecture of a neural network and the choice of its activation function are both fundamental to its performance. Equally important is ensurin

safetyarxiv-cs-lg

From Rubble Simulation to Active Magnetic Mapping: Quantum Sensing for Disaster Response

arXiv:2606.25957v1 Announce Type: new Abstract: Locating survivors of building collapses within the first 72 hours is a critical challenge in disaster response, and existing sensing modalities provide

researcharxiv-cs-ro

Gastroendoscopy View Synthesis: A New Real Dataset and Evaluation

arXiv:2606.25427v1 Announce Type: new Abstract: Novel view synthesis (NVS) is an active research topic in computer vision, owing to the success of neural radiance field (NeRF) and 3D Gaussian splattin

Geometry-Anchored Transport Framework for Exemplar-Free Class-Incremental Learning

arXiv:2606.25347v1 Announce Type: cross Abstract: Exemplar-free class-incremental learning (EFCIL) requires stable decision boundaries within a shifting feature space. While maintaining class-conditio

safetyarxiv-cs-cv

GeoRanker: Distance-Aware Ranking for Worldwide Image Geolocalization

arXiv:2505.13731v4 Announce Type: replace Abstract: Worldwide image geolocalization-the task of predicting GPS coordinates from images taken anywhere on Earth-poses a fundamental challenge due to the

GUI agent: Guided Exploration of User-Sensitive Screens

arXiv:2606.25705v1 Announce Type: new Abstract: LLM agents are increasingly being used to automate tasks for users within an open GUI environment. They inevitably encounter screens containing user-sen

safetyarxiv-cs-ai

HG-Bench: A Benchmark for Multi-Page Handwritten Answer-Region Grounding in Automated Homework Assessment

model-releasesarxiv-cs-cv

arXiv:2606.25491v1 Announce Type: new Abstract: Automated homework assessment depends not only on recognizing student answers, but also on accurately locating where each answer and each intermediate r

Applications

HiFiVe: High-Fidelity Vehicle Generation Leveraging Auto-Regressive 2D Generative Priors

arXiv:2606.25300v1 Announce Type: new Abstract: Existing 3D vehicle generation methods often suffer from low geometric fidelity and blurry textures, hindering their downstream applications. While rece

applicationsarxiv-cs-cv

How Small Can 6G Reason? Scaling Tiny-to-Small Language Models for AI-Native Networks

model-releasesarxiv-cs-ai

arXiv:2603.02156v2 Announce Type: replace-cross Abstract: Emerging 6G visions, reflected in ongoing standardization efforts within 3GPP, IETF, ETSI, ITU-T, and the O-RAN Alliance, increasingly charact

Hybrid-IR: Dual-Path Hybrid Retrieval with Iterative Reasoning for Complex Medical Question Answering

arXiv:2606.25338v1 Announce Type: new Abstract: Large language models (LLMs) have shown promising performance across a wide range of biomedical applications, including medical question answering (QA),

Local Ai

Hypergraph Normal World Models for Logical Visual Anomaly Detection

arXiv:2606.25368v1 Announce Type: new Abstract: Visual anomaly detection is often deployed with only normal training images. Most one-class detectors map test patches or features to a normal reference

local-aiarxiv-cs-cv

Invisible to humans, visible to machines: a preregistered audit of Unicode fidelity across four biomedical bibliographic APIs

arXiv:2606.24897v1 Announce Type: cross Abstract: Biomedical text mining, scientometrics, and the construction of training corpora for biomedical large language models (LLMs) all assume that the abstr

KidRisk: Benchmark Dataset for Children Dangerous Action Recognition

model-releasesarxiv-cs-cv

arXiv:2606.25298v1 Announce Type: new Abstract: Children are naturally energetic, and during their spontaneous activities, they often encounter potentially dangerous situations, especially when lackin

Latent Block-Diffusion Temporal Point Processes: A Semi-Autoregressive Framework for Asynchronous Event Sequence Generation

arXiv:2606.24982v1 Announce Type: new Abstract: Modeling and sampling from the underlying distribution of asynchronous event sequences are crucial in various real-world applications, including social

Learning Optimization Proxies for Sequential Contextual Stochastic Programs: An Order Fulfillment Application

arXiv:2606.25362v1 Announce Type: cross Abstract: Sequential contextual stochastic programs model real-time decision systems in which each time epoch commits to an action under uncertainty whose conse

safetyarxiv-cs-lg

Learning to Erase Private Knowledge from Multi-Documents for Retrieval-Augmented Large Language Models

arXiv:2504.09910v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) is a promising technique for applying LLMs to proprietary domains. However, retrieved documents may contain sen

Lightweight PCGAE-Net: Parallel CrossGate Attention and Bottleneck AutoEncoder for Efficient 5G Channel Prediction

arXiv:2606.25401v1 Announce Type: cross Abstract: Accurate channel state information (CSI) prediction is essential for proactive beamforming and resource management in 5G massive MIMO systems, yet the

safetyarxiv-cs-ai

LLM Performance on a Real, Double-Marked GCSE Benchmark

model-releasesarxiv-cs-cl

arXiv:2606.24973v1 Announce Type: new Abstract: We introduce a dataset of 32,534 double-marked real student responses to GCSE mock exams (GCSEs are the UK's national exams, taken at age ~16), spanning

MedGuards: Multi-Agent System for Reliable Medical Error Detection and Correction

arXiv:2606.25651v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed in healthcare settings, accurate error detection and correction in generated or existing text

safetyarxiv-cs-cl

MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation

arXiv:2606.26016v1 Announce Type: new Abstract: Normalizing Flows (NFs) are powerful generative models capable of exact density estimation and sampling. However, their strict invertibility often force

Minimalist Preprocessing Approach for Image Synthesis Detection

arXiv:2606.25297v1 Announce Type: new Abstract: Generative models have significantly advanced image generation, resulting in synthesized images that are increasingly indistinguishable from authentic o

Model Forensics: Investigating Whether Concerning Behavior Reflects Misalignment

arXiv:2606.26071v1 Announce Type: new Abstract: A central goal of safety research is determining whether a model is misaligned. Prior work has largely focused on detecting concerning behavior. But beh

Agents

New research from Meta. Building synthetic training data has stayed a fixed pipeline that you hand-tune and then freeze. Autodata casts an A…

New research from Meta. Building synthetic training data has stayed a fixed pipeline that you hand-tune and then freeze. Autodata casts an AI agent as a data scientist that builds training and evaluat

agentsdair-ai--x

Optimizing Abstractive Summarization With Fine-Tuned PEGASUS

arXiv:2606.25462v1 Announce Type: new Abstract: Abstractive text summarization is the technique of generating a short and concise summary comprising the salient ideas of a source text without making a

Overview of HIPE-2026: Person-Place Relation Extraction from Multilingual Historical Texts

arXiv:2606.25935v1 Announce Type: new Abstract: Was this person ever at that place, and if so, when? Answering such questions from noisy, multilingual historical documents is the central challenge of

Power-Budgeted Underwater Vehicle Control via Constrained Reinforcement Learning

arXiv:2606.25680v1 Announce Type: new Abstract: Underwater vehicles operate from a fixed onboard energy budget that propulsion rapidly depletes, so a controller that completes its task while drawing l

safetyarxiv-cs-ro

Privacy Vulnerabilities of Attention Layers in Tabular Foundation Models and Protection of High-Risk Queries

arXiv:2606.26021v1 Announce Type: cross Abstract: Tabular foundation models are commonly assumed to present limited privacy concerns as they are often pre-trained on large collections of synthetic dat

researcharxiv-cs-ai

Agents

Probabilistic Agents in Deterministic Audits: Evaluating Multi-Agent Systems for Automated Audits Based on the German IT-Grundschutz

arXiv:2606.25622v1 Announce Type: cross Abstract: The NIS-2 Directive mandates robust Risk Management from thousands of small and medium enterprises. To ensure compliance, companies rely on establishe

agentsarxiv-cs-ai

PVF:Understanding AI Vulnerability Against SDCs

arXiv:2405.01741v4 Announce Type: replace-cross Abstract: Reliability of AI systems is a fundamental concern for the successful deployment and widespread adoption of AI technologies. Unfortunately, th

Agents

RAVEN: Long-Horizon Reasoning & Navigation with a Visuo-Spatio-Temporal Memory

arXiv:2606.25206v1 Announce Type: cross Abstract: Long-term robot deployment requires a compact and scalable memory that preserves fine-grained visual semantics, grounds observations in space and time

agentsarxiv-cs-cl

Recursive QLSTM with Dynamic Variational Quantum Circuit Adaptation

arXiv:2606.24932v1 Announce Type: cross Abstract: Recent advances in quantum computing and machine learning have motivated the development of quantum models for sequential data processing. In this pap

researcharxiv-cs-lg