AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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3,366 papers
DAMP uses both quantization-error energy and decay-based persistence to identify high-risk channels during offline calibration and stores these channels at higher precision and the remainder in INT8, the first to study post-training quantization of recurrent states in GDN and KDA based language models.
It is found that cue-based prompting can influence multilingual sentence-level Easy-to-Read simplification, but its benefits are modest, metric-dependent, and language-dependent.
It is shown that AI generation leaves a consistent ``stylometric footprint'': a small subset of features, primarily entropy and lexical diversity, consistently separates AI-generated text from human writing across 8 LLMs and 5 domains, while the remaining features depend heavily on the domain and generator.
It is found that the speculative-decoding module in recent LLMs can be repurposed for efficient high-quality classification by appending a trained soft prompt at the end of the target sequence, which can repurpose the speculative-decoding module into a sequence classifier.
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STITCH is presented, a training-free method that divides a video into semantically meaningful temporal chunks that are computed once per video and reused across tasks, suggesting that reusable temporal abstraction is a promising direction for general video understanding.
The Confidence-Weighted Numeric Precision Score (\cwnps), which aggregates three calibrated detectors and discounts uncertain proposals, is proposed for scalable evaluation and developed a process model in which requested instances compete for a finite set of resolvable image regions.
The results support the common principle that explicit regulation of neuron utilization and effective connectivity can improve the emergence of generalizable internal computation and motivate broader investigation of biologically inspired activity regulation and adaptive sparsification, including in large language mode...
This work proposes a comprehensive pipeline for improving financial QA systems through high-quality synthetic data generation and fine-tuning of smaller language models (SLMs) using Quantized Low-Rank Adaptation (QLoRA).
Foundation machine learning interatomic potentials (MLIPs) deliver near-ab-initio accuracy at a fraction of the computational cost, yet their promise for Metal-organic Frameworks (MOFs) remains largely unrealized as large unit cells make first-principles training data expensive to generate, fine-tuned models are scarce...
This method learns permanent handoff policies from accumulated trajectory evidence and Teacher-Annotated Censored Intervention Times (TACIT) and represents each annotation as an interval-censored observation on a cumulative-risk scale and achieves the highest held-out success among learned policies on both ALFWorld and...
For institution-constrained clinical QA, in-domain teacher-supervised fine-tuning was the most reliable evaluated adaptation path, and public-benchmark transfer was not a dependable proxy for local utility in the primary internal comparison.
Summary Background Recent NIH Data Management and Sharing (DMS) policy updates and NIH controlled-access data security requirements have increased attention to facial anonymization and controlled-access handling of shared head imaging data. This is particularly relevant for datasets submitted to or hosted by the Cancer...
A Blog post by Liquid AI on Hugging Face
Genie 4: our new world model unlocking unprecedented realism in real-time simulation.
Generative AI
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
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