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.
Agent Trading Arena trains LLMs in real-time financial markets to improve numerical reasoning.
Survey examines LLMs in financial trading.
The authors propose a parametric model called the arena model for prediction in paired competitions, i.e. paired comparisons with eliminations and bifurcations. The arena model has a number of appealing advantages. First, it predicts the results of competitions without rating many individuals. Second, it takes full adv…
Foresight Arena benchmarks AI forecasting on real-world markets, isolating predictive edge.
LUNA improves linear attention for long sequences without sacrificing accuracy.
The potential of machine learning to automate and control nonlinear, complex systems is well established. These same techniques have always presented potential for use in the investment arena, specifically for the managing of equity portfolios. In this paper, the opportunity for such exploitation is investigated throug…
We present NAVREN-RL, an approach to NAVigate an unmanned aerial vehicle in an indoor Real ENvironment via end-to-end reinforcement learning RL. A suitable reward function is designed keeping in mind the cost and weight constraints for micro drone with minimum number of sensing modalities. Collection of small number of…
Dropping a tiny fraction of preferences can significantly alter the rankings of top LLMs.
Unified framework to bridge human and LLM judgments.
DBOT uses AI to automate long-term stock valuation.
We define the surface complex for -manifolds and embark on a case study in the arena of Seifert fibered spaces. The base orbifold of a Seifert fibered space captures some of the topology of the Seifert fibered space, so, not surprisingly, the surface complex of a Seifert fibered space always contains a subcomplex is…
Multiplayer Online Battle Arena (MOBA) games are among the most played digital games in the world. In these games, teams of players fight against each other in arena environments, and the gameplay is focused on tactical combat. Mastering MOBAs requires extensive practice, as is exemplified in the popular MOBA Defence o…
Improved Mamba model for long-range sequence tasks.
Statistical framework improves LLM chatbot ranking.
In this paper, using Riemann-Lagrange geometrical methods, we construct a geometrical model on 1-jet spaces for the study of multi-time relativistic magnetized non-viscous plasma, characterized by a given energy-stress-momentum distinguished (d-) tensor. In that arena, we give the conservation laws and the continuity e…
Develops a new method for quantizing rough volatility for volatility derivatives pricing.
SAttention improves long sequence attention with smoothed skeleton sketching.
In this paper, it is elaborated the theory the Ricci flows for manifolds enabled with nonintegrable (nonholonomic) distributions defining nonlinear connection structures. Such manifolds provide a unified geometric arena for nonholonomic Riemannian spaces, Lagrange mechanics, Finsler geometry, and various models of grav…
Study uses machine learning and PolyModel to improve hedge fund performance.
The techniques of deep learning have become the state of the art methodology for executing complicated tasks from various domains of computer vision, natural language processing, and several other areas. Due to its rapid development and promising benchmarks in those fields, researchers started experimenting with this t…
Low-rank framework for task-specific LLM ranking from sparse comparisons.
The problem of data uncertainty has motivated the incorporation of robust optimization in various arenas, beyond the Markowitz portfolio optimization. This work presents the extension of the robust optimization framework for the minimization of downside risk measures, such as Value-at-Risk (VaR) and Conditional Value-a…
MIMONets speed up neural network inference by processing multiple inputs in parallel.
Paper proposes a method to predict MOBA game winners with calibrated confidence.
Skeinformer accelerates self-attention for long sequences with linear complexity.
Progress in multiagent intelligence research is fundamentally limited by the number and quality of environments available for study. In recent years, simulated games have become a dominant research platform within reinforcement learning, in part due to their accessibility and interpretability. Previous works have targe…
Automated model tracks mouse behavior in home cages.
The automatic and efficient discovery of skills, without supervision, for long-living autonomous agents, remains a challenge of Artificial Intelligence. Intrinsically Motivated Goal Exploration Processes give learning agents a human-inspired mechanism to sequentially select goals to achieve. This approach gives a new p…
Paper introduces a new method for Transformers with linear complexity.
We present a generalization of Minkowski's classic theorem on the reconstruction of tetrahedra from algebraic data to homogeneously curved spaces. Euclidean notions such as the normal vector to a face are replaced by Levi-Civita holonomies around each of the tetrahedron's faces. This allows the reconstruction of both s…
Decades of research on the neural code underlying spatial navigation have revealed a diverse set of neural response properties. The Entorhinal Cortex (EC) of the mammalian brain contains a rich set of spatial correlates, including grid cells which encode space using tessellating patterns. However, the mechanisms and fu…
Skyformer uses Gaussian kernel and Nyström method to speed up self-attention in transformers.
A drone catches another agile drone using competitive reinforcement learning.
New optimizer MARS-M combines variance reduction with Muon for faster LLM training.
In many developing countries intellectual property infringement and the commerce of pirate goods is an entrepreneurial activity. Digital piracy is very often the only media for having access to music, cinema, books and software. At the same time, bio-prospecting and infringement of indigenous knowledge rights by intern…
This study explores Kaluza-Klein reductions of new maximally supersymmetric backgrounds.
A purely algebraic construction of super-energy tensors for arbitrary fields is presented in any dimensions. These tensors have good mathematical and physical properties, and they can be used in any theory having as basic arena an n-dimensional manifold with a metric of Lorentzian signature. In general, the completely …
MARS optimizes large model training by reducing variance, outperforming AdamW.
This paper studies transformer learning dynamics and initialization.
Multiplayer Online Battle Arena (MOBA) is currently one of the most popular genres of digital games around the world. The domain of knowledge contained in these complicated games is large. It is hard for humans and algorithms to evaluate the real-time game situation or predict the game result. In this paper, we introdu…
Study of 2d gauged linear sigma models to derive difference equations and spectral data.
HOPE improves SSMs for long-memory tasks with robust initialization and training.
A denoising algorithm seeks to remove noise, errors, or perturbations from a signal. Extensive research has been devoted to this arena over the last several decades, and as a result, today's denoisers can effectively remove large amounts of additive white Gaussian noise. A compressed sensing (CS) reconstruction algorit…
This paper examines how regional trade agreements affect global trade relationships.
CJE calibrates cheap LLM judges against an oracle, achieving high accuracy at a fraction of the cost.
SSMs have a built-in bias towards low-frequency components, which can be adjusted.
Paper predicts international trade flows using machine learning and factorization models.
Traders in a stock market exchange stock shares and form a stock trading network. Trades at different positions of the stock trading network may contain different information. We construct stock trading networks based on the limit order book data and classify traders into classes using the -shell decomposition m…