Search: “safety”

How Environment and Urbanization Shape Bird Diversity in Sri Lanka

arXiv:2607.00582v1 Announce Type: cross Abstract: This study presents a comprehensive analysis of bird diversity across Sri Lanka by integrating spatial, temporal, and environmental data. Bird observa

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

HyFL-CLIP: Hyperbolic Fine-Tuning of CLIP for Robust Long-Context Understanding

DGX agent

arXiv:2607.00428v1 Announce Type: new Abstract: CLIP (Contrastive Language-Image Pre-training) has become a de facto paradigm for image-text alignment, but it struggles with long-context descriptions

safetyarxiv-cs-cv

2 Jul 2026

Identifying Latent Concepts and Structures for Generalized Category Discovery

arXiv:2607.00620v1 Announce Type: cross Abstract: Generalized Category Discovery (GCD) aims to recognize known classes while autonomously discovering novel ones in open-world settings. However, curren

KungfuBot: Physics-Based Humanoid Whole-Body Control for Learning Highly-Dynamic Skills

arXiv:2506.12851v3 Announce Type: replace-cross Abstract: Humanoid robots are promising to acquire various skills by imitating human behaviors. However, existing algorithms are only capable of trackin

Learning Category-level Last-meter Navigation from RGB Demonstrations of a Single-instance

arXiv:2512.11173v4 Announce Type: replace Abstract: Achieving precise positioning of the mobile manipulator's base is essential for successful manipulation actions that follow. Most of the RGB-based n

Learning Generalizable Skill Policy with Data-Efficient Unsupervised RL

arXiv:2607.00392v1 Announce Type: cross Abstract: Unsupervised Reinforcement Learning (URL) aims to pre-train scalable, skill-conditioned policies without extrinsic rewards, serving as a foundation fo

Learning User-Aware Recall: Personalized Retrieval in Long-Term Conversational Memory

arXiv:2607.00017v1 Announce Type: cross Abstract: Long-term conversational agents are expected to remember past interactions, but memory is useful only when the right evidence is recalled for the righ

LIST3R: Long-sequence Instance-aware 3D Reconstruction

arXiv:2607.00375v1 Announce Type: new Abstract: We present LIST3R, an instance-aware framework for long-sequence 3D reconstruction inspired by the way humans organize spatial memory around stable and

Measuring Dead Directions: Decomposing and Classifying Singular Structure off Canonical Alignment

arXiv:2607.00603v1 Announce Type: new Abstract: We give a descent-free, alignment-free measurement of singular structure on trained networks. At a single frozen checkpoint the read recovers the order

MedCAGD: Context-Aware Gated Decoder for Efficient Medical Image Segmentation

arXiv:2607.00409v1 Announce Type: new Abstract: Medical image segmentation relies on the ability of encoder-decoder architectures to translate rich feature representations into accurate pixel-level pr

Meta-Transfer Learning for mmWave Beam Alignment

arXiv:2607.00860v1 Announce Type: cross Abstract: Millimeter-wave (mmWave) beam alignment plays a critical role in next-generation wireless systems, yet its efficient implementation remains challengin

Mirror-Fusion Attention for Reflection-Aware Self-Supervised Representation Learning

arXiv:2607.00850v1 Announce Type: new Abstract: Most self-supervised learning (SSL) methods encourage invariance across augmentations, but strict flip invariance can suppress informative left--right c

MoVA: Learning Asymmetric Dual Projections for Modular Long Video-Text Alignment

arXiv:2607.00858v1 Announce Type: new Abstract: Contrastive pre-training has propelled video-text alignment, yet models often inherit the critical limitations of their image-text predecessors like CLI

Multi-scale Mixture of World Models for Embodied Agents in Evolving Environments

arXiv:2607.00457v1 Announce Type: new Abstract: Embodied agents operating in the real world require multi-scale reasoning and knowledge adaptation as conditions change. We identify two challenges in a

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning

arXiv:2505.19614v2 Announce Type: replace-cross Abstract: Multimodal learning has seen remarkable progress, particularly with large-scale pre-training across various modalities. Most current approache

NeuroCogMap Reveals Cognitive Organization of Large Language Models

arXiv:2607.00397v1 Announce Type: cross Abstract: Understanding how complex cognitive functions are organized within artificial systems is central to interpreting large language models (LLMs) and rela

OmniView-Space: Reinforcing Spatial Reasoning via Multi-Perspective Spatial Mapping

arXiv:2607.00881v1 Announce Type: new Abstract: Spatial intelligence remains a persistent challenge for Multimodal Large Language Models (MLLMs), as it requires coherent spatial scene representations

OpenReward: Learning to Reward Long-form Agentic Tasks via Reinforcement Learning

arXiv:2510.24636v3 Announce Type: replace Abstract: Reward models (RMs) have become essential for aligning large language models (LLMs), serving as scalable proxies for human evaluation in both traini

PAPA: Online Personalized Active Preference Alignment

arXiv:2607.00486v1 Announce Type: cross Abstract: Diffusion models are highly effective at modeling complex data distributions, including images and text. However, in applications like personalized re

Personalization as Inverse Planning: Learning Latent Design Intents for Agentic Slide Generation via Structural Denoising

arXiv:2607.00407v1 Announce Type: new Abstract: Slide design requires personalizing both deck themes and page layouts. Yet, current AI agent-based methods struggle with fine-grained, page-level design

Predicting LLM Reasoning Performance with Small Proxy Model

arXiv:2509.21013v4 Announce Type: replace-cross Abstract: Given the prohibitive cost of pre-training large language models, it is essential to leverage smaller proxy models to optimize datasets before

Prior-Anchored Debiasing for Long-Tailed Multi-Organ Pathology Report Generation

arXiv:2607.00499v1 Announce Type: new Abstract: Automated pathology report generation from Whole Slide Images (WSIs) has attracted increasing attention in digital pathology. However, existing methods

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition

arXiv:2607.00358v1 Announce Type: new Abstract: Electroencephalogram (EEG) captures endogenous brain activity with high temporal fidelity and holds substantial promise for precise emotion decoding. Ho

Prompt Optimization for User Simulation in Conversational Recommender Systems: A Multi-Objective Framework

arXiv:2607.00010v1 Announce Type: cross Abstract: Conversational recommender systems (CRSs) are a core component of next-generation intelligent recommender systems because they enable users to activel

Prompt2Effect: Training-Free Image-to-Video Model Specialization via LoRA Generation

arXiv:2606.13971v2 Announce Type: replace Abstract: While personalizing Image-to-Video (I2V) diffusion models with specific visual effects is increasingly demanded for high-end generation, current pra

QuasiMoTTo: Quasi-Monte Carlo Test-Time Scaling

arXiv:2607.01179v1 Announce Type: cross Abstract: Scaling inference compute, by generating many parallel attempts per problem, is a costly but reliable lever for improving language model capabilities.

Real-Time Hard Negative Sampling via LLM-based Clustering for Large-Scale Two-Tower Retrieval

arXiv:2607.00448v1 Announce Type: cross Abstract: The two-tower model has been widely used for large-scale recommendation systems, particularly in the retrieval stage. Industry standards for training

Revisiting Autoregressive Models for Generative Image Classification

arXiv:2603.19122v2 Announce Type: replace Abstract: Class-conditional generative models have emerged as accurate and robust classifiers, with diffusion models demonstrating clear advantages over other

Robots Ask the Way: Communication-Enabled Social Navigation

arXiv:2607.01044v1 Announce Type: new Abstract: Assistive autonomous robots operating in multi-agent environments require efficient strategies to locate specific individuals among multiple residents.

RoboWorld: Fast and Reliable Neural Simulators for Generalist Robot Policy Evaluation

arXiv:2607.01060v1 Announce Type: new Abstract: Video world models are emerging as a scalable alternative for evaluating generalist robot policies, bypassing the physical constraints and engineering b

Salt: Self-Consistent Distribution Matching with Cache-Aware Training for Fast Video Generation

arXiv:2604.03118v2 Announce Type: replace Abstract: Distilling video generation models to extremely low inference budgets (e.g., 2--4 NFEs) is crucial for real-time deployment, yet remains challenging

Selective Expert Guidance for Effective and Diverse Exploration in Reinforcement Learning of LLMs

arXiv:2510.04140v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a widely adopted technique for enhancing the reasoning ability of Large Language Mo

Selective Test-Time Debiasing for CLIP via Reward Gating

arXiv:2607.00423v1 Announce Type: new Abstract: Vision language models (VLMs) demonstrate strong zero-shot performance, but often perpetuate social stereotypes in person-centric queries, yielding skew

Self-Evolving Agents with Anytime-Valid Certificates

arXiv:2607.00871v1 Announce Type: new Abstract: Self-evolving agents violate the assumption behind most learning-theoretic guarantees: the data, evaluator, components, and hypothesis space are produce

Semi-Bandit Learning for Monotone Stochastic Optimization

arXiv:2312.15427v3 Announce Type: replace Abstract: Stochastic optimization is a widely used approach for optimization under uncertainty, where uncertain input parameters are modeled by random variabl

Sequentially-Controlled Interactive Multi-Particle Flow-Maps for Online Feedback-Driven Search

arXiv:2607.01144v1 Announce Type: cross Abstract: While generative models have enabled training-free reward alignment, current methods typically excel in local exploration within narrow regions of the

SleepLM: Natural-Language Intelligence for Human Sleep

arXiv:2602.23605v2 Announce Type: replace Abstract: We present SleepLM, a family of sleep-language foundation models that enable human sleep alignment, interpretation, and interaction with natural lan

Spatio-Temporal Gaussian Process for Building Terrain-Incorporating Wind Power Curves

arXiv:2607.00051v1 Announce Type: cross Abstract: Accurate modeling of wind turbine power curves is crucial for optimal wind farm operation. Nearly all existing power curve models focus on temporal va

Speech Playground: An Interactive Tool for Speech Analysis and Comparison

arXiv:2607.00418v1 Announce Type: new Abstract: This paper presents Speech Playground, an interactive speech visualization and comparison tool. While existing tools such as Praat are excellent, it can

Staleness-Learning Rate Scaling Laws for Asynchronous RLHF

arXiv:2607.01083v1 Announce Type: cross Abstract: High-throughput RLHF systems often decouple rollout generation from policy optimization, leading to the use of stale rollouts during learner updates.

TetraSDF: Analytic Isosurface Extraction with Multi-resolution Tetrahedral Grid

arXiv:2511.16273v2 Announce Type: replace Abstract: Extracting an explicit surface that exactly matches the zero-level set of a neural signed distance function (SDF) remains challenging. Sampling-base

Towards an automated AI-based framework for floor plan compliance checks for residential buildings

arXiv:2607.00015v1 Announce Type: cross Abstract: To improve residents' well-being in Australia's urban areas, governments have introduced policy reforms such as SEPP65, BADS, and SPP7.3 to enhance ap

Training-Free Debiasing of Diffusion Models via CLIP-Guided Denoising Optimization

arXiv:2607.00817v1 Announce Type: new Abstract: Text-to-image diffusion models achieve impressive visual quality, yet demographic bias remains a challenge, as neutral prompts consistently produce ster

Two AI Metrics Diverged: Will it Make All the Difference?

arXiv:2607.00913v1 Announce Type: new Abstract: As exponential compute scaling continues, will the capabilities of frontier AI models outstrip what is accessible to developers on a small fixed budget?

Understanding Why Language Models Hallucinate: Testing Reasoning Against Priors

arXiv:2607.00447v1 Announce Type: new Abstract: Large language models often produce hallucinated answers that violate prompt-level constraints. A key diagnostic question is whether these failures refl

Unleashing More Actions via Action Compositional Training for VLA Models

arXiv:2607.00351v1 Announce Type: new Abstract: Vision-Language-Action models excel at robotic manipulation, driven by the scale and diversity of demonstration data. However, standard training paradig

Verifiable Rewards for Calibrated Probabilistic Forecasting

arXiv:2607.00164v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards can in principle train calibrated probabilistic forecasters, since a proper scoring rule such as the Brie

VideoSearch-R1: Iterative Video Retrieval and Reasoning via Soft Query Refinement

arXiv:2607.00446v1 Announce Type: cross Abstract: As video corpora continue to expand in both scale and task complexity, there is increasing demand for approaches that retrieve relevant videos from la