· ai
[Paper] RELIC: Interactive Video World Model with Long-Horizon Memory
A truly interactive world model requires three key ingredients: real-time long-horizon streaming, consistent spatial memory, and precise user control. However, ...
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- · ai
[Paper] Fast & Efficient Normalizing Flows and Applications of Image Generative Models
This thesis presents novel contributions in two primary areas: advancing the efficiency of generative models, particularly normalizing flows, and applying gener...
- · ai
[Paper] Domain Feature Collapse: Implications for Out-of-Distribution Detection and Solutions
Why do state-of-the-art OOD detection methods exhibit catastrophic failure when models are trained on single-domain datasets? We provide the first theoretical e...
- · ai
[Paper] Jina-VLM: Small Multilingual Vision Language Model
We present Jina-VLM, a 2.4B parameter vision-language model that achieves state-of-the-art multilingual visual question answering among open 2B-scale VLMs. The ...
- · ai
[Paper] Large Language Models for Limited Noisy Data: A Gravitational Wave Identification Study
This work investigates whether large language models (LLMs) offer advantages over traditional neural networks for astronomical data processing, in regimes with ...
- · ai
[Paper] PSA: Pyramid Sparse Attention for Efficient Video Understanding and Generation
Attention mechanisms are the core of foundation models, but their quadratic complexity remains a critical bottleneck for scaling. This challenge has driven the ...
- · ai
[Paper] TARA Test-by-Adaptive-Ranks for Quantum Anomaly Detection with Conformal Prediction Guarantees
Quantum key distribution (QKD) security fundamentally relies on the ability to distinguish genuine quantum correlations from classical eavesdropper simulations,...
- · ai
[Paper] Efficient Public Verification of Private ML via Regularization
Training with differential privacy (DP) provides a guarantee to members in a dataset that they cannot be identified by users of the released model. However, tho...
- · ai
[Paper] On the Temporality for Sketch Representation Learning
Sketches are simple human hand-drawn abstractions of complex scenes and real-world objects. Although the field of sketch representation learning has advanced si...
- · ai
[Paper] Teaching Old Tokenizers New Words: Efficient Tokenizer Adaptation for Pre-trained Models
Tokenizer adaptation plays an important role in transferring pre-trained language models to new domains or languages. In this work, we address two complementary...
- · ai
[Paper] Is Lying Only Sinful in Islam? Exploring Religious Bias in Multilingual Large Language Models Across Major Religions
While recent developments in large language models have improved bias detection and classification, sensitive subjects like religion still present challenges be...
- · devops
[Paper] OD-MoE: On-Demand Expert Loading for Cacheless Edge-Distributed MoE Inference
Mixture-of-Experts (MoE), while offering significant advantages as a Large Language Model (LLM) architecture, faces substantial challenges when deployed on low-...