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Multifingered grasping is a crucial robotic skill, but current deep-learning grasp planners often struggle to general...
Modern LLM agents are often improved by modifying prompts, tools, or workflows manually, while the executable scaffol...
LLM coding agents issue Bash commands through interfaces that may serialize, wrap, and reparse model output. Matched ...
Long-horizon robot manipulation requires a robot to both execute individual skills reliably and sequence them coheren...
Should you replace your text-embedding pipeline with a large language model? We answer this with a controlled, cost-a...
We introduce TinyCast, an attention-free zero-shot forecaster that emits a predictive distribution from 146,505 param...
Large language model agents can adapt to complex tasks by constructing workflows at inference time, but procedures di...
Anatomically plausible segmentation remains challenging because of low contrast, ambiguous boundaries, and modality-s...
The standard objection to full automation is demand-side: if humans earn nothing, who buys the output? This confuses ...
Multimodal large language models (MLLMs) combine linguistic reasoning with visual perception, yet their ability to pe...
X-band SAR satellites (8-12 GHz) play a critical role in disaster response, environmental monitoring, and military in...
Reasoning language models trained with reinforcement learning typically operate under a fixed token budget rather tha...