Decision models offered resource advantages alongside lower peak accuracy; generative large language model configurations offered resource advantages alongside lower peak accuracy; selecting models for medical workflows requires considering probability quality and repeatability together with accuracy and the resources...
O. Freyer, D. Glauert, M. Hofmann et al.· 0 citations
This work proposes user behaviour fuzzing, a guided search over plausible user behaviours that can lead a model to violate its role specification, and introduces RoleFUZZER, a framework that adapts coverage-guided fuzzing from software testing to operationalise the search.
Kshitish Ghate, Michael Stephen Saxon, Tadayoshi Kohno et al.· 0 citations
Predicting medical item difficulty from item text alone remains challenging. Prior work has largely relied on linguistic features or text representations derived from general-purpose and domain-specific language models, but predictive performance has remained modest. This study takes a different approach by using diffi...
Xiaomeng Xiong, Marcus Walker, Yanlin Jiang· 0 citations
The external sources retained in our non-systematic audit did not isolate the incremental security or utility effect of consuming /llms.txt while ordinary retrieval remained fixed. The initial audit covered 39 sources through August 16, 2026, with later targeted updates through October 14. A purposive 15-tool study obs...
Gang-Zhen Qian, Kai-Nan Zhou, Chu-Hong Xu et al.· 0 citations
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Reliable legal information retrieval must ground legal reasoning in authoritative statutory sources. In Arabic judicial settings, long factual narratives must be mapped to concise articles that express abstract legal rules, creating a narrative-to-legal-rule abstraction gap. Using a benchmark of 200 synthetic Saudi Ara...
Quarterly earnings forecasting requires an agent to connect financial evidence to the income-statement line items that produce a company's reported earnings. We introduce EPSBench, a benchmark for studying this ability across 149 firm-quarters from 86 US companies. Agents read a fixed collection of filings, earnings-ca...
Yanbin Yin, Chuyu Xu, Liqin Ye et al.· 0 citations
Text summarization is an important task for advancing natural language processing (NLP) research and applications in Indic languages. Despite progress in extractive and abstractive summarization, both monolingual summarization (MS) and cross-lingual summarization (CLS) remain relatively underexplored for these language...
EasyProver is presented, a Lean proving system built from recursive agents with isolated contexts, asynchronous search, parallel tactic probing, and an elastic elaboration service, and Aegis is introduced, which converts competitive programming problems into much harder verification tasks over real implementations.
Debargha Ganguly, Divya Raghunathan, Dejan Jovanovic et al.· 0 citations
It is found that a model can recognize an impossible design when asked only whether it is feasible, yet accept the same design, reporting"solved", when asked for a full answer, when asked for a full answer.
We introduce Nemotron 3.5 Super and Nemotron 3.5 Lightning, open and efficient Mixture-of-Experts Hybrid Mamba-Transformer models designed for reasoning, long-context understanding, and agentic workloads. Super is a 120B-parameter, 12B-active multimodal model, while Lightning is a smaller 30B-parameter, 3B-active text...
NVIDIA, :, Aastha Jhunjhunwala et al.· 0 citations
LLM-as-a-Judge has become a standard for evaluating large language models, yet most approaches implicitly assume that a single judge prompt functions as a stable evaluation instrument. Prior work has primarily explored deliberate prompt modifications such as scoring rubrics, role descriptions, or chain-of-thought reaso...
Ilija Subasic, Brett Levert, Andrew Rabinovich et al.· 0 citations
Sparse autoencoders (SAEs) can predict internal features associated with model errors, but association alone does not establish causal influence. We study this distinction in multiple-choice question answering, where answer preference can be measured by the logit margin between the correct answer and the competing choi...
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.
