4,422+ open-access research outputs.
Identity verification is a critical gateway to accessing government services and public benefits, yet contemporary systems are typically designed around visual interaction, leaving blind and low visio…
Preserving affective nuance remains a challenge in Machine Translation (MT), where semantic equivalence often takes precedence over emotional fidelity. This paper evaluates the performance of three st…
Digital computing-in-memory (DCIM) has emerged as a promising solution for large language model (LLM) acceleration by minimizing data transfers between external DRAM and on-chip accelerators while mai…
Generative AI tools are widely used by youth and have introduced new privacy and safety challenges. While prior research has explored youth's safety in GenAI within western context, it often overlooks…
We analyse Compton-thick active galactic nuclei (CT AGNs), a heavily obscured subclass that challenges traditional X-ray diagnostics. Using 243 sources from the 70-Month \textit{SWIFT}/BAT catalogue (…
Fitness tracking platforms increasingly integrate generative AI to interpret activity data, such as Strava's Athlete Intelligence. These integrations raise questions about how athletes engage with AI-…
As generative voice models are rapidly advancing in both capabilities and public utilization, the unconsented collection, reuse, and synthesis of voice data are introducing new classes of privacy, sec…
The growing availability of online support groups has opened up new windows to study mental health through natural language processing (NLP). However, it is hindered by a lack of high-quality, well-va…
The concept of homophily is pervasive in online social media. While many empirical studies have relied on external sociodemographic traits to investigate it, significantly less is known about homophil…
We construct mean spectral energy distributions (SEDs) for a substantial sample of 56,969 Sloan Digital Sky Survey DR16 quasars with $z < 0.75$, utilizing multiwavelength data from the mid-infrared (M…
We investigate whether explicit belief graphs improve LLM performance in cooperative multi-agent reasoning. Through 3,000+ controlled trials across four LLM families in the cooperative card game Hanab…
Emerging AI systems in behavioral health and psychiatry use multi-step or multi-agent LLM pipelines for tasks like assessing self-harm risk and screening for depression. However, common evaluation app…
Large language models (LLMs) possess strong persuasive capabilities that outperform humans in head-to-head comparisons. Users report consulting LLMs to inform major life decisions in relationships, me…
Recent work has used LLM agents to reproduce empirical social science results with access to both the data and code. We broaden this scope by asking: Can they reproduce results given only a paper's me…
Moltbook, a Reddit-style social platform launched in January 2026 for AI agents, has attracted over 2.3 million posts and 14 million comments within its first two months. We analyze a dataset of 2.19 …
We introduce MMTR-Bench, a benchmark designed to evaluate the intrinsic ability of Multimodal Large Language Models (MLLMs) to reconstruct masked text directly from visual context. Unlike conventional…
We show that pre-training a Transformer on music before language significantly accelerates language acquisition. Using piano performances (MAESTRO dataset), a developmental pipeline -- music $\to$ poe…
The first step in any genome assembly algorithm entails the conversion from the domain of strings and overlaps to the language of graphs and paths, typically using one of the two conventional methods:…
Content moderation systems are typically evaluated by measuring agreement with human labels. In rule-governed environments this assumption fails: multiple decisions may be logically consistent with th…
In this note we consider a two-dimensional semi-discrete dislocation energy and propose a simple and physically motivated construction for the grain boundary between two crystal grains with a small or…
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