AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,089 papers
MemeBridge, a curated dataset centered on U.S.-originated memes, is introduced, designed to capture two complementary perspectives: how Chinese participants interpret these memes, and how U.S. participants anticipate how people from other cultures might misunderstand them.
A two-level hierarchical reinforcement learning (HRL) framework for conversational agents that bridges the gap between existing token-level and utterance-level RL methods and introduces a dual-granularity reward mechanism that combines the utterance-level satisfaction score with token-level intrinsic self-consistency a...
It is shown that commonly used EEG features can reveal participant identity and demographic attributes in addition to supporting the intended cognitive task, motivating purpose-limited representations and explicit privacy auditing in wearable neurohealth systems.
Anamnesis produces opinion distributions that more closely match real-world survey data than standard persona-prompting baselines, offering a transparent, reproducible, and open-source alternative to proprietary simulation services.
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DigitalCoach, a multimodal dataset of 72 human expert-novice computer use coaching sessions consisting of 22,752 dialogue turns grounded in 28.1 hours of screen and input event recordings across five software applications, evaluates whether state-of-the-art models can teach humans how to use computers.
Generativism is proposed as a learning theory for the generative AI age and offers a foundation for rethinking instructional design, learning, assessment, and expertise development in contexts where generative AI plays an integral role in cognition.
An emotion-planning framework that determines the emotion prior to the textual generation, grounding the downstream emotional TTS in a streaming manner, and finally implements an entire streaming pipeline for real-time deployment.
This experiment examined how algorithmic advice affects human behavior in a classic economic game with a unique, non-collusive, and analytically traceable equilibrium, finding that algorithmic advice can function as a strategic signal, shaping coordination even without explicit communication.
We introduce Unsupervised Partner Design (UPD), a population-free multi-agent reinforcement learning method for robust ad-hoc teamwork. UPD generates training partners on-the-fly and selects them adaptively based on a learnability criterion, removing the need for pre-trained partner populations or manual parameter tuni...
These findings show that participants configured proactive support through prospective planning, used suggestions for both idea generation and self-monitoring, and valued lightweight visual representations alongside non-directive rhetorical framing for non-intrusive interventions.
The results show strong performance on colonoscopy images and competitive performance on prostate MRI, supporting gaze-guided prototype refinement as a promising approach for segmentation-label-efficient, human-in-the-loop medical image segmentation.
A disclosure gate conditioning information release on the companion agent's behaviour is answered, with a disclosure gate conditioning information release on the companion agent's behaviour: its state is a ladder of five ordered gates, merged onto three observable depth layers.
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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