Deploying adaptive intelligence at the edge remains challenging due to the high computational and energy cost of training neural models. Spiking Neural Networks...
Optimization problems in real-world applications across the medical and engineering domains often involve potential risks when evaluating candidate solutions. S...
!https://cdn.platum.kr/wp-content/uploads/2026/05/unnamed-1-5-735x1024.jpg 프로그램 개요 딥테크 액셀러레이터 블루포인트파트너스가 글로벌 헬스케어 기업 인바디와 함께 헬스케어 및 라이프스타일 분야의 예비·초기 창업자를 발굴한다....
Retrieval-augmented generation RAG has become the de facto standard for grounding large language models LLMs in private data. The standard architecture — chunki...
learning data science in 2020, Pandas was one of the most popular tools. Although new tools focus on improving Pandas’ weaknesses in handling very large dataset...
Von Economo neurons (VENs) are selectively lost in behavioural-variant frontotemporal dementia (bvFTD) and reduced in autism spectrum conditions (ASC), yet thei...
This study develops and evaluates a deep reinforcement learning framework for dynamic portfolio allocation across global equity markets. The Soft Actor-Critic a...
For AI systems to keep improving in knowledge work, they need either a reliable mechanism for autonomous self-improvement or human evaluators capable of catchin...
The Manta Ray Foraging Optimization algorithm (MRFO) has proven to be a powerful heuristic strategy in the optimal solution of a large number of engineering pro...
. A part of me started this journey because data engineering is one of the hottest and highest-paying careers right now. I’m not going to pretend that wasn’t a...
, you will learn what Recursive Language Models RLMs are, why they are winning all the long-context benchmarks right now, and understand how they are different...
OpenAI OpenAI and the Government of Malta are today announcing a world’s first partnership to roll out ChatGPT Plus to all Maltese citizens. The initiative will...
The company formerly known as Intercom just did something that no major customer service platform has attempted at scale: it built an AI agent whose sole job is...
One of the key challenges of current multi-agent AI systems is that they communicate by generating and sharing text sequences, which introduces latency, drives...
Reconstructing coherent 3D geometry and appearance from unposed multi-view images is a fundamental yet challenging problem in computer vision. Most existing vis...
Demand for AI accelerators is rapidly increasing rack power density, with projections approaching 1MW per deployment by 2027. This poses a major challenge for d...
Distribution utilities are now expected to deliver bills that customers can actually read attach a defensible carbon number to every kWh sold and schedule load ...
Generative artificial intelligence (AI) is increasingly integrated into the online platforms where humans exchange opinions; large language models (LLMs) now po...
Billion-parameter Vision-Language-Action (VLA) policies have recently shown impressive performance in robotic manipulation, yet their size and inference cost re...
We introduce a dynamics-level approach to watermarking generative models. Rather than embedding signals into model weights or outputs, we embed the watermark di...
Probabilistic forecasting of infectious diseases is crucial for public health but relies on labor-intensive manual model curation by expert modeling teams. This...
When researchers ask whether two transformer layers are 'equivalent' for compression, they often conflate distinct tests. Replacement asks whether one layer's m...
Can LLM agents improve decision-making through self-generated memory without gradient updates? We propose FORGE (Failure-Optimized Reflective Graduation and Evo...
The accelerating convergence of smart metering, generative artificial intelligence, and quantum-inspired combinatorial optimisation is reshaping how energy util...
Magnetic order is a fundamental property of materials, governing collective behavior and enabling a broad range of functionalities. Yet magnetic structure remai...
Generative video models are increasingly used in design animation tasks, yet no standardized evaluation framework exists for this domain. Unlike natural video g...
Aphasias, selective language impairments which can arise from brain damage, reveal the functional organization of human language by providing causal links betwe...
Differential privacy changes the effective sample size governing CVaR learning. For tail mass τ, the privacy-relevant sample size is not n, but nτ; equivalently...
Deep research agents have achieved remarkable progress on complex information seeking tasks. Even long ReAct style rollouts explore only a single trajectory, wh...
Clinical decision support systems (CDSS) require scrutable, auditable pipelines that enable rigorous, reproducible validation. Yet current LLM-based CDSS remain...
Traditional scientific modeling typically begins with fixed, instance-wise effective equations and then carries out equation-specific analysis and computation, ...
Effective tutoring requires distinguishing optimal, valid but suboptimal, and incorrect student solutions, a distinction central to intelligent tutoring systems...
Deploying compound LLM agents in adversarial, partially observable sequential environments requires navigating several design dimensions: (1) what the agent see...
Second-order methods offer an attractive path toward more sample-efficient LLM training, but their practical use is often blocked by the systems cost of maintai...
Agricultural landscape segmentation in the Global South is challenging as it is characterized by fragmented plots, high intra-class variance, and a scarcity of ...
Few-shot Generalist Anomaly Detection requires models to generalize to novel categories without retraining, posing significant challenges in real-world scenario...
Autoregressive next-token training offers a unified formulation for image generation and text understanding, but it also creates strong modality competition tha...
New VB Pulse data shows Microsoft and OpenAI leading enterprise agent orchestration, but Anthropic’s first measurable foothold points to a larger fight over who...
Vision Transformers (ViTs) are known to exhibit high-norm patch-token outliers that degrade feature map quality, a problem effectively mitigated by register tok...
Generating simulation-ready tabletop scenes from task instructions is an intriguing and promising research direction in the field of Embodied AI. However, exist...
While multi-modal 3D semantic occupancy prediction typically enhances robustness by fusing camera and LiDAR inputs, its effectiveness is fundamentally constrain...
Diffusion-based image synthesis has made AI-generated images (AIGI) increasingly photorealistic, raising urgent concerns about authenticity in applications such...
We propose a scalable neuromorphic architecture based on spiking dynamics emerging from the autonomous time-continuous evolution of clockless (asynchronous) dig...
Semantic code search has been widely adopted in both academia and industry. These approaches embed natural-language queries and code snippets into a shared embe...
articles on techniques I apply when using Claude Code to get the most out of it. However, a topic I’ve spent less time covering is how to improve my Claude Code...
We introduce thermodynamic networks, a general framework for autonomous, physics-based computation using non-equilibrium steady states. These networks are model...
. Primarily, I work with my coding assistant in Chinese. However, my writing is often mixed: many engineering terms are more familiar to me in English especiall...
manager. Your team has just spent three weeks refactoring the prompt chain for your company’s internal AI research agent. They deploy the new version to a stagi...
