A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
This thesis evaluates text-based vs audio-based classification of mental health interviews.
Improved negation detection in Dutch clinical texts using machine learning.
Information extraction is an important task in NLP, enabling the automatic extraction of data for relational database filling. Historically, research and data was produced for English text, followed in subsequent years by datasets in Arabic, Chinese (ACE/OntoNotes), Dutch, Spanish, German (CoNLL evaluations), and many …
Contemporary debates on filter bubbles and polarization in public and social media raise the question to what extent news media of the past exhibited biases. This paper specifically examines bias related to gender in six Dutch national newspapers between 1950 and 1990. We measure bias related to gender by comparing loc…
Study on efficiency of Dutch auctions on blockchains considering various parameters.
New measure predicts Dutch housing market downturns.
Paper finds Dutch Draw optimal baseline for binary classification.
This paper examines three independent explanatory variables and their relation with cost overrun in order to decide whether this is different for Dutch infrastructure projects compared to worldwide findings. The three independent variables are project type (road, rail, and fixed link projects), project size (measured i…
Solves the Sleeping Beauty problem as a 'thirder' using the Kelly Criterion.
West Frisian lemmatizer, POS tagger, and parser created.
Cost overruns in transport infrastructure projects know no geographical limits, overruns are a global phenomenon. Nevertheless, the size of cost overruns varies with location. In the Netherlands, cost overruns appear to be smaller compared to the rest of the world. This paper tests whether Dutch projects perform signif…
Using a methodology similar to that used the in the worldwide research, the cost performance of Dutch large-scale transport infrastructure projects is determined. In the Netherlands, cost overruns are as common as cost underruns but because cost overruns are larger than cost underruns projects on average have a cost ov…
Study optimal auction formats for maximizing MEV on Ethereum.
Thomas Rot discusses a topology theorem at a math conference.
Spectral analysis detects structural changes in financial networks.
Develops a method to optimize tax codes with practical constraints.
We construct two examples of shareholder networks in which shareholders are connected if they have shares in the same company. We do this for the shareholders in Turkish companies and we compare this against the network formed from the shareholdings in Dutch companies. We analyse the properties of these two networks in…
Paper presents a universal baseline for binary prediction models.
Conditional random fields (CRFs) have been shown to be one of the most successful approaches to sequence labeling. Various linear-chain neural CRFs (NCRFs) are developed to implement the non-linear node potentials in CRFs, but still keeping the linear-chain hidden structure. In this paper, we propose NCRF transducers, …
In this paper we study speaker linking (a.k.a.\ partitioning) given constraints of the distribution of speaker identities over speech recordings. Specifically, we show that the intractable partitioning problem becomes tractable when the constraints pre-partition the data in smaller cliques with non-overlapping speakers…
In many contexts, it can be useful for domain experts to understand to what extent predictions made by a machine learning model can be trusted. In particular, estimates of trustworthiness can be useful for fraud analysts who process machine learning-generated alerts of fraudulent transactions. In this work, we present …
Detects out-of-distribution sentences in Neural Machine Translation.
The financial crisis clearly illustrated the importance of characterizing the level of 'systemic' risk associated with an entire credit network, rather than with single institutions. However, the interplay between financial distress and topological changes is still poorly understood. Here we analyze the quarterly inter…
Quasi-experimental research designs, such as regression discontinuity and interrupted time series, allow for causal inference in the absence of a randomized controlled trial, at the cost of additional assumptions. In this paper, we provide a framework for discontinuity-based designs using Bayesian model comparison and …
Efficient methods estimate bid and value distributions in auctions.
Dynamic rule-based investment strategies outperform static ones in pension schemes.
Economic integration, globalization and financial crises represent examples of processes whose understanding requires the analysis of the underlying network structure. Of particular interest is establishing whether a real economic network is in a state of (quasi)stationary equilibrium, i.e. characterized by smooth stru…
Proposes hedging strategies for mortgage prepayment risk.
We introduce the general arbitrage-free valuation framework for counterparty risk adjustments in presence of bilateral default risk, including default of the investor. We illustrate the symmetry in the valuation and show that the adjustment involves a long position in a put option plus a short position in a call option…
On July 26, 1995, at the University of California, Santa Cruz, a young Dutch mathematician by the name Aise Johan de Jong made a revolution in the study of the arithmetic, geometry and cohomology theory of varieties in positive or mixed characteristic. The talk he delivered, first in a series of three entitled "Dominat…
New ASR system handles multiple languages without needing language-specific encoding.
Study quantifies gender bias in language models across 7 languages.
Paper reviews neurolinguistics and language technologies, emphasizing mutual enrichment.
Our analysis of financial data, in terms of super-exponential growth, suggests that the seed of the 2002/03 crisis of the Dutch supermarket giant AHOLD was planted in 1996. It became quite visible in 1999 when the post-bubble destabilization regime was well-developed and acted as the precursor of an inevitable collapse…
New technique reduces language biases in large language models.
When a bilingual student learns to solve word problems in math, we expect the student to be able to solve these problem in both languages the student is fluent in,even if the math lessons were only taught in one language. However, current representations in machine learning are language dependent. In this work, we pres…
Paper introduces TrufLL for language model training without labeled data.
System identifies language of transliterated text.
LLMs translate natural language trading intents into correct option strategies using a domain-specific language.
New findings show language models can't simultaneously avoid hallucinations and capture all language richness.
This paper proposes a new method to connect language and physical actions in reinforcement learning.
Julia accelerates machine learning in various fields with balance of efficiency and simplicity.
Neural language modeling (LM) has led to significant improvements in several applications, including Automatic Speech Recognition. However, they typically require large amounts of training data, which is not available for many domains and languages. In this study, we propose a multilingual neural language model archite…
Proposes using Wasserstein barycenter for better multilingual alignment.
Improved power arbitrage through domain-adapted reinforcement learning.
The paper applies math and physics to language models, introducing entropy and geometric concepts.
Urbanism is no longer planned on paper thanks to powerful models and 3D simulation platforms. However, current work is not open to the public and lacks an optimisation agent that could help in decision making. This paper describes the creation of an open-source simulation based on an existing Dutch liveability score wi…
Multilingual end-to-end (E2E) models have shown great promise in expansion of automatic speech recognition (ASR) coverage of the world's languages. They have shown improvement over monolingual systems, and have simplified training and serving by eliminating language-specific acoustic, pronunciation, and language models…