Category
9,261 papers
Improving an existing methodology with a required control, an instruction-tuned model is compared against three RLVR agents trained from it, on four question-answering datasets, using only free-tier Kaggle GPUs.
It is argued that LLM-based AI systems answer political questions for hundreds of millions of people is a set of policies over whom to answer, what to say, and whether to engage at all, conditional on the topic and what the system knows about the user.
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...
Reach audiences
Advertise in front of researchers, engineers, and readers.
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...
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.
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...
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...
A Blog post by Ai2 on Hugging Face
A Blog post by IBM Research on Hugging Face
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.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
