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Machine Heart
Machine Heart
Apr 11, 2026 · Artificial Intelligence

How PiLoT Enables Monocular Drones to Navigate 10 km Drift‑Free and Lock onto Targets

PiLoT, a CVPR 2026 Highlight paper, introduces a neural pixel‑to‑3D registration framework that lets a single‑camera UAV achieve drift‑free 6‑DoF pose and real‑time target locking over 10 km without GNSS, running at 25‑30 FPS on an NVIDIA Jetson Orin and outperforming existing hybrid and absolute‑pose methods.

GNSS-denied navigationPiLoTReal-time Inference
0 likes · 12 min read
How PiLoT Enables Monocular Drones to Navigate 10 km Drift‑Free and Lock onto Targets
Data Party THU
Data Party THU
Sep 21, 2025 · Artificial Intelligence

How the New ECD Dataset Supercharges Multimodal LLM Chart Understanding

The paper introduces the Effective Chart Dataset (ECD), a large, high‑quality, diverse synthetic chart collection and the ECDBench benchmark, detailing a five‑stage modular synthesis pipeline, extensive QA generation, and experiments that show consistent performance gains for open‑source multimodal large language models on chart‑understanding tasks.

AIChart UnderstandingMLLM
0 likes · 9 min read
How the New ECD Dataset Supercharges Multimodal LLM Chart Understanding
Data Party THU
Data Party THU
Jul 30, 2025 · Artificial Intelligence

Can Graph Neural Networks Accurately Predict Antibody‑Antigen Binding Affinity?

A recent Oxford study introduces Graphinity, an equivariant graph neural network that directly uses antibody‑antigen structures to predict ΔΔG, achieving up to r = 0.89 on large synthetic datasets, but reveals that data volume and diversity, rather than model architecture, remain the primary bottleneck for reliable affinity prediction.

Protein Engineeringantibody affinitygraph neural networks
0 likes · 7 min read
Can Graph Neural Networks Accurately Predict Antibody‑Antigen Binding Affinity?
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Mar 15, 2024 · Artificial Intelligence

Why Arithmetic Feature Interaction Is Key to Deep Tabular Learning

Researchers from Alibaba Cloud AI and Zhejiang University present AMFormer, a Transformer‑based model that incorporates arithmetic feature interaction, demonstrating superior fine‑grained modeling, sample efficiency, and generalization on synthetic and real‑world tabular datasets, establishing a new state‑of‑the‑art in deep tabular learning.

AMFormerTransformerdeep learning
0 likes · 12 min read
Why Arithmetic Feature Interaction Is Key to Deep Tabular Learning