3 papers
cs.CL2025
Knowledge-Instruct: Effective Continual Pre-training from Limited Data using Instructions
Oded Ovadia, Meni Brief, Rachel Lemberg +1
While Large Language Models (LLMs) acquire vast knowledge during pre-training, they often lack domain-specific, new, or niche information. Continual pre-training (CPT) attempts to…
cs.AI2025
SECQUE: A Benchmark for Evaluating Real-World Financial Analysis Capabilities
Noga Ben Yoash, Meni Brief, Oded Ovadia +4
We introduce SECQUE, a comprehensive benchmark for evaluating large language models (LLMs) in financial analysis tasks. SECQUE comprises 565 expert-written questions covering SEC f…
cs.AI2024
Mixing It Up: The Cocktail Effect of Multi-Task Fine-Tuning on LLM Performance -- A Case Study in Finance
Meni Brief, Oded Ovadia, Gil Shenderovitz +3
The application of large language models (LLMs) in domain-specific contexts, including finance, has expanded rapidly. Domain-specific LLMs are typically evaluated based on their pe…