· ai
[Paper] TAB-DRW: A DFT-based Robust Watermark for Generative Tabular Data
The rise of generative AI has enabled the production of high-fidelity synthetic tabular data across fields such as healthcare, finance, and public policy, raisi...
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- · ai
[Paper] Visualizing LLM Latent Space Geometry Through Dimensionality Reduction
Large language models (LLMs) achieve state-of-the-art results across many natural language tasks, but their internal mechanisms remain difficult to interpret. I...
- · ai
[Paper] MoGAN: Improving Motion Quality in Video Diffusion via Few-Step Motion Adversarial Post-Training
Video diffusion models achieve strong frame-level fidelity but still struggle with motion coherence, dynamics and realism, often producing jitter, ghosting, or ...
- · ai
[Paper] On the Limits of Innate Planning in Large Language Models
Large language models (LLMs) achieve impressive results on many benchmarks, yet their capacity for planning and stateful reasoning remains unclear. We study the...
- · ai
[Paper] Model-Based Policy Adaptation for Closed-Loop End-to-End Autonomous Driving
End-to-end (E2E) autonomous driving models have demonstrated strong performance in open-loop evaluations but often suffer from cascading errors and poor general...
- · ai
[Paper] Learning When to Stop: Adaptive Latent Reasoning via Reinforcement Learning
Latent reasoning represents a new development in Transformer language models that has shown potential in compressing reasoning lengths compared to chain-of-thou...
- · ai
[Paper] Multimodal Robust Prompt Distillation for 3D Point Cloud Models
Adversarial attacks pose a significant threat to learning-based 3D point cloud models, critically undermining their reliability in security-sensitive applicatio...
- · ai
[Paper] Self-Transparency Failures in Expert-Persona LLMs: A Large-Scale Behavioral Audit
If a language model cannot reliably disclose its AI identity in expert contexts, users cannot trust its competence boundaries. This study examines self-transpar...
- · ai
[Paper] RoParQ: Paraphrase-Aware Alignment of Large Language Models Towards Robustness to Paraphrased Questions
Large Language Models (LLMs) often exhibit inconsistent behavior when answering paraphrased questions, suggesting a reliance on surface-level patterns rather th...
- · ai
[Paper] UAVLight: A Benchmark for Illumination-Robust 3D Reconstruction in Unmanned Aerial Vehicle (UAV) Scenes
Illumination inconsistency is a fundamental challenge in multi-view 3D reconstruction. Variations in sunlight direction, cloud cover, and shadows break the cons...
- · ai
[Paper] Machine Learning Approaches to Clinical Risk Prediction: Multi-Scale Temporal Alignment in Electronic Health Records
This study proposes a risk prediction method based on a Multi-Scale Temporal Alignment Network (MSTAN) to address the challenges of temporal irregularity, sampl...
- · ai
[Paper] VacuumVLA: Boosting VLA Capabilities via a Unified Suction and Gripping Tool for Complex Robotic Manipulation
Vision Language Action models have significantly advanced general purpose robotic manipulation by harnessing large scale pretrained vision and language represen...