8 results for "valuation multiple"
Sources: Anthropic could raise a new $50B round at a valuation of $900B
The maker of Claude has received multiple pre-emptive offers at valuations in the $850 billion to $900 billion range, according to sources familiar with the matter.…
Expert Evaluation of LLM's Open-Ended Legal Reasoning on the Japanese Bar Exam Writing Task
Large language models (LLMs) have shown strong performance on legal benchmarks, including multiple-choice components of bar exams. However, their capacity for generating open-ended legal reasoning in …
Multi-Dimensional Evaluation of Sustainable City Trips with LLM-as-a-Judge and Human-in-the-Loop
Evaluating nuanced conversational travel recommendations is challenging when human annotations are costly and standard metrics ignore stakeholder-centric goals. We study LLMs-as-Judges for sustainable…
Agentic clinical reasoning over longitudinal myeloma records: a retrospective evaluation against expert consensus
Multiple myeloma is managed through sequential lines of therapy over years to decades, with each decision depending on cumulative disease history distributed across dozens to hundreds of heterogeneous…
Ten fast-growing Canadian companies at reasonable valuations
Investors increasingly want exposure to companies that are still growing rapidly but trade at multiples that leave room for further upside…
An empirical evaluation of the risks of AI model updates using clinical data: stability, arbitrariness, and fairness
Artificial Intelligence and Machine Learning (AI/ML) models used in clinical settings are increasingly deployed to support clinical decision-making. However, when training data become stale due to cha…
Applied AI-Enhanced RF Interference Rejection
AI-enhanced interference rejection in radio frequency (RF) transmissions has recently attracted interest because deep learning approaches trained on both the signal of interest (SOI) and the signal mi…
PivotMerge: Bridging Heterogeneous Multimodal Pre-training via Post-Alignment Model Merging
Multimodal Large Language Models (MLLMs) rely on multimodal pre-training over diverse data sources, where different datasets often induce complementary cross-modal alignment capabilities. Model mergin…