25 papers
SigmaScale: LLM Compression with SVD-based Low-Rank Decomposition and Learned Scaling Matrices
Ernests Lavrinovics, Marco Letizia, Roy Janco +3
We present SigmaScale, a method for learning auxiliary scaling matrices to aid truncated Singular Value Decomposition (SVD) based Large Language Model (LLM) compression. Instea…
HiFi-KPI: A Dataset for Hierarchical KPI Extraction from Earnings Filings
Rasmus Aavang, Rasmus T. Aavang, Giovanni Rizzi +5
Accurate tagging of earnings reports can yield significant short-term returns for stakeholders. The machine-readable inline eXtensible Business Reporting Language (iXBRL) is mandat…
When Discourse Pressures Conflict: Information Structure in Vision-Language Model Outputs
Marcell Fekete, Johannes Bjerva, Tamás Káldi
Vision-language models (VLMs) are increasingly evaluated for whether they identify the right visual content, but little is known about whether they express such content in a discou…
Effective Performance Measurement: Challenges and Opportunities in KPI Extraction from Earnings Calls
Rasmus T. Aavang, Rasmus Tjalk-Bøggild, Alexandre Iolov +3
Earnings calls are a key source of financial information about public companies. However, extracting information from these calls is difficult. Unlike the templatic filings require…
How Good is Your Wikipedia? Auditing Data Quality for Low-resource and Multilingual NLP
Kushal Tatariya, Artur Kulmizev, Wessel Poelman +6
Wikipedia's perceived high quality and broad language coverage have established it as a fundamental resource in NLP. However, in recent years, such assumptions of high quality have…
Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model Factuality
Mike Zhang, Johannes Bjerva, Russa Biswas
We introduce fs1, a simple yet effective method that improves the factuality of reasoning traces by collecting them from large reasoning models and grounding them in knowledge grap…