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2,089 papers
It is found that LLMs outperform expectations at replicating comment structure and formality, but struggle to accurately capture nuanced emotions, e.g. understating joy and overstating anger.
Building effective AI systems increasingly depends on writing high-quality task requirements, yet users often struggle to articulate the constraints, preferences, and edge cases that determine success. This problem is especially acute in AI development, where behavior is shaped not only by human expectations but also b...
It is argued that for applications processing sensitive user data (medical, legal, journalistic, or personal), the Web-CLI should be the default architecture, as it makes data locality an independently verifiable technical property rather than a policy promise.
A provenance-aware pipeline that converts task telemetry and human-authored reports into a shared typed task-state representation, aligns and reconciles their facts, detects conflicts, and generates structured handover reports supports provenance-aware state reconciliation as a design pattern for safer AI-assisted hand...
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This work model the AI-mediated process of writing a student--instructor email at the highest level of involvement, and compares it with an unaided model of writing the same messages, built from participants' accounts and a classic model of the writing process.
A minimal seven-field curatable record is derived and complementary responsibilities for model hubs, scholarly indexes, and digital libraries are derived, providing practical guidance for improving the preservation and bibliographic control of open LLM artifacts.
Data Characters is introduced, a visualization approach that represents affective content in journaling through human-like characters and investigates the potential of character-based representations for conveying affective experiences and explores what visual encodings emerge through customization.
A preliminary framework for analyzing adaptability in cooperative games by conceptualizing adaptive stimuli as retrieval or disruption of players'ludic knowledge is presented and offered an initial vocabulary for describing how cooperative games can be designed to create demands for team adaptation.
Human-like cognition does not select past experience by topical similarity alone: affective significance and unresolved conflict also shape what becomes accessible. We present PsychoAgent, a cognitive architecture for LLM agents that separates factual and affective memory and integrates both through a conflict-aware ex...
The AppraiSal benchmark is introduced, containing 996 emotional support conversations with human-annotated mental states, including salient cognitive appraisal dimensions, and PRISM, a multi-agent probabilistic framework grounded in Bayesian Inverse Planning, designed to improve LLMs'ability to identify context-specifi...
It is argued that public tutoring benchmarks can better support positive-impact evaluation by reporting solving-oriented and pedagogy-oriented scores separately and by making disclosure-sensitive, student-agency-preserving criteria more explicit.
LALS (Latent Association Leaning Score) is introduced, a zero-shot metric that projects visual-token activations into the model's text-embedding space to measure concept associations per token and layer and shows that culturally loaded visual cues further modulate these internal associations.
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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