AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,089 papers
GNN-VIEW exposes the graph's information pathways, allowing model developers to debug the graph structure before training and after training, GNN-VIEW uses attribution-based explainability to reveal which input features are used by the trained model for a given forecast.
In autonomous driving, robot teleoperation serves as a critical safety fallback mechanism, requiring operators to assume direct control in the event of system failure. While recent research has pivoted toward high-level supervisory control or simulation-based studies, these approaches often fail to capture the physical...
This work explores a multimodal approach to the alignment of the behavior of open-ended learning autonomous robots with human purposes through the use of large language models as cultural enablers. While autonomous robots can generate their own skills and goals through interaction with the environment, they often lack...
Experts can master fine hand-object manipulation skills, yet limited conscious perception of rapid tactile interactions hinders their ability to articulate the underlying control mechanisms. Badminton racket control requires rapid, fine hand-force coordination, providing a demanding testbed for uncovering these mechani...
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Targeted controls show that tool-invocation scores alone do not establish event grounding and that reminder coverage depends on response history and frequency, and motivate developing and evaluating streaming assistants for timely action, initiative under general user needs, and coverage of entire response sequences.
The emergence of artificial intelligence (AI) coding agents has put pull requests under pressure: agents open millions of pull requests per month, while some open-source projects have begun to restrict or disable external contributions. We investigate which alternatives to pull requests practitioners are proposing or a...
Assistive agents in shared-control settings face a dual challenge: acting proactively to align with the human's intentions while remaining legible enough for the human to comprehend and fluently respond in real time. We present Dream2Assist, a model-based reinforcement learning framework for tightly-coupled shared deci...
With the rise of Large Language Models (LLMs), software developers are presented with a powerful new approach: delegating software development tasks to LLMs. Existing studies have explored task delegation for a subset of tasks and factors. Critically, what tasks developers delegate to LLMs, to what extent, and why they...
Sustained attention is critical for academic performance, yet existing auditory support tools are static and not grounded in real-time neural evidence. This paper presents EEGBiFormer, a hybrid CNN-Transformer model for realtime binary classification of attention states, focus versus nonfocus, from 16-channel EEG signa...
Intelligent tutoring systems (ITSs) have advanced learner motivation and personalization in cognitive domains, but extending these gains to psychomotor tasks remains challenging. Existing psychomotor ITSs rely on learner models built before instruction or updated once per module, leaving open how to use real-time asses...
Integration of artificial intelligence (AI) technology into identity workflows, such as automated face recognition (FR), has enhanced operational capabilities, with FR algorithms achieving super-human scale and accuracy. However, these gains can make human oversight of FR more difficult, raising questions about the eff...
Although learning design (LD) plays a central role in shaping online courses, large-scale empirical evidence on how courses are actually structured remains scarce, and existing analytics work has characterised courses through student engagement with specific learning activities rather than through indicators of the des...
AI agents can generate code at a scale that’s hard for humans to review line-by-line. PDD Kit helps ensure the code is doing what the developer intended by creating formal specifications and testing against them. It converts developer intent into a Verus specification, proves AI-generated code meets it for every input, and uses tests where proofs aren't practical. Developers review intent, not every line. The post Formally verifying agent-written full-stack web apps with PDD Kit appeared first o…
Data Mining & Modeling
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
During the School of Humanities, Arts, and Social Sciences’ 75th Anniversary Symposium, President Sally Kornbluth said “MIT has never needed your particular insight and guidance more than we do now.”
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
“X-Hinges” helps design and 3D print items like lamps and gloves with an interactive twist: automatically embedded sensors that perceive and adaptively respond to human contact.
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