Multilingual code language models transfer skills across programming languages (PLs), but whether any PL occupies a privileged pivot position remains contested: geometric analyses point to C-family languages and Go, while behavioral evidence highlights Python. We revisit this question under controls for representationa...
AMUSER is presented, a multimodal framework which simulates user behaviour and automatically generates prioritised UX improvement recommendations from resulting data and suggests an asymmetric role of multimodality: visual access during simulation improves recommendations through richer traces, while providing visual i...
Anurupa Chowdhury, Bin Wu, Hossein A. Rahmani et al.· arXiv.org· 0 citations
Large language models (LLMs) increasingly mediate human decisions and communication, yet their behavioural regularities remain difficult to characterize systematically. We develop a cross-linguistic psychometric profiling framework and evaluate nine LLMs using seven psychological instruments, with five repeated adminis...
Non-technical stakeholders frequently cannot write the SQL needed to extract insights from operational databases. We built and evaluated a Text-to-SQL agent that closes this gap end to end: a six-node LangGraph StateGraph checks question relevance, fetches the live schema, generates PostgreSQL, validates it with a dry...
A methodology is implemented for evaluating large language models on sequential triage, the task of predicting a triage acuity label from a growing prefix of a nurse-patient conversation, which shows that the label at every checkpoint is anchored on the chief complaint exchanges, and prompting interventions fail to lif...
Dipankar Srirag, Hao-Kai Zhao, Ashutosh Kumar et al.· 0 citations
Semantic-Geometric Decoupled Routing is proposed, a training-free block routing framework that shifts semantic aggregation to the pre-RoPE space and reconstructs geometric bias with an offline structural prior and relative block distances and yields an explicit closed-form block routing score without token-level search...
This work demonstrates that traditional single- and multi-reference training paradigms are suboptimal for natural language generation tasks and provides empirical evidence that consolidating diverse references into a unified training signal is crucial for developing effective systems.
Maitreya Prafulla Chitale, Ketaki Shetye, Yash More et al.· 0 citations
Dialectal Arabic machine translation (MT) remains challenging despite recent progress in Arabic language technologies, particularly because effective translation requires modeling not only semantic content but also dialectal variation, conversational context, speaker and addressee characteristics, and sociolinguistic a...
Abdellah El Mekki, AbdelRahim A. Elmadany, Samar M. Magdy et al.· 1 citation
LLM-based machine translation evaluation can closely match human judgments, but in practice it remains largely diagnostic, with the signals rarely translating into direct quality improvements under real production constraints. We propose a two-stage, evaluator-guided automatic post-editing framework that turns MQM-styl...
Multimodal large language models (MLLMs) are increasingly used as evaluators, yet their reliability in professional assessment tasks that require expert judgment remains unclear. We investigate this challenge in the context of assessing psychotherapeutic interpersonal skills and introduce MIS-Bench, a Multimodal Interp...
This paper presents our system for Track 2 of the NLPCC 2026 Shared Task 10 on citation-level faithfulness in AI-assisted scientific reporting. Given an atomic scientific claim and the structured full text of its cited paper, the task requires both a four-way relation label and up to three evidence paragraph identifier...
This work presents a pipeline and conversational system that combines geographic entity resolution, topic modeling, sentiment analysis, and Retrieval-Augmented Generation over 22,788 chunks of YouTube transcripts and comments spanning 309 North American cities and shows that ROUGE-1-based groundedness is a paraphrase-d...
J. Morales, Monica Hegde, Fayeq Jeelani Syed· 0 citations
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.