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.
LATM framework uses LLMs to create and reuse tools for efficient problem-solving.
We propose a tool-use model that can detect the features of tools, target objects, and actions from the provided effects of object manipulation. We construct a model that enables robots to manipulate objects with tools, using infant learning as a concept. To realize this, we train sensory-motor data recorded during a t…
New findings show tool-augmented models can recall unlimited facts, outperforming purely memorized models.
UniFeat is an open-source Java tool for feature selection.
A study ranks critical Lean Six Sigma tools for implementation in Portuguese companies.
Interactive tool helps RL researchers debug and understand their models.
Survey of tools for studying hierarchical hyperbolic spaces.
ToolChain-CRC addresses the risk-control problem for retrieval-augmented and tool-using agents under drift.
Survey of software developers' experience with Github Copilot tool.
In manufacture, steel and other metals are mainly cut and shaped during the fabrication process by computer numerical control (CNC) machines. To keep high productivity and efficiency of the fabrication process, engineers need to monitor the real-time process of CNC machines, and the lifetime management of machine tools…
New L0 norm added to TDA for market analysis.
Tool manipulation is vital for facilitating robots to complete challenging task goals. It requires reasoning about the desired effect of the task and thus properly grasping and manipulating the tool to achieve the task. Task-agnostic grasping optimizes for grasp robustness while ignoring crucial task-specific constrain…
We examined the use of three conventional anomaly detection methods and assess their potential for on-line tool wear monitoring. Through efficient data processing and transformation of the algorithm proposed here, in a real-time environment, these methods were tested for fast evaluation of cutting tools on CNC machines…
FiNCAT tool automatically identifies financial numerals in documents.
Develops tools to audit ML models for bias and unfairness.
New methods improve tool-to-tool matching in semiconductor manufacturing.
Data science teams collaborate extensively, using various tools and stakeholders.
One of the open challenges in designing robots that operate successfully in the unpredictable human environment is how to make them able to predict what actions they can perform on objects, and what their effects will be, i.e., the ability to perceive object affordances. Since modeling all the possible world interactio…
Long non-coding RNAs (lncRNAs) are a class of non-coding RNAs which play a significant role in several biological processes. RNA-seq based transcriptome sequencing has been extensively used for identification of lncRNAs. However, accurate identification of lncRNAs in RNA-seq datasets is crucial for exploring their char…
TIR expands LLM capabilities by enabling problem-solving strategies.
Third part of a study on liquidity risk in asset management, focusing on managing the asset-liability liquidity risk.
Interview study reveals considerations for designing semi-automated bias detection tools.
Python tools for 3D shape analysis on Kendall's space.
Gaussian processes (GP) are powerful tools for probabilistic modeling purposes. They can be used to define prior distributions over latent functions in hierarchical Bayesian models. The prior over functions is defined implicitly by the mean and covariance function, which determine the smoothness and variability of the …
Deep neural nets classify tool wear in blanking processes.
The paper examines how macroeconomic control tools lost effectiveness, leading to a 'dark ages' period.
SafePILCO is a Python tool for safe reinforcement learning.
In this paper we explore the richness of information captured by the latent space of a vision-based generative model. The model combines unsupervised generative learning with a task-based performance predictor to learn and to exploit task-relevant object affordances given visual observations from a reaching task, invol…
Teaching tool simplifies Monte Carlo simulation for project risk analysis.
Develops a tool to identify abnormal blood smear results based on CBC tests.
Digital tools may hinder or facilitate multidisciplinary collaboration in occupational health.
The present contribution suggests the use of a multidimensional scaling (MDS) algorithm as a visualization tool for manifold-valued elements. A visualization tool of this kind is useful in signal processing and machine learning whenever learning/adaptation algorithms insist on high-dimensional parameter manifolds.
A key challenge in developing and deploying Machine Learning (ML) systems is understanding their performance across a wide range of inputs. To address this challenge, we created the What-If Tool, an open-source application that allows practitioners to probe, visualize, and analyze ML systems, with minimal coding. The W…
New tools explain FRF model predictions in high-dimensional ECG data.
Paper introduces ML tools for guided wave behaviour in composite materials.
Optimizes risk assessment tools using mixed-integer programming.
Several recent papers in digital topology have sought to obtain fixed point results by mimicking the use of tools from classical topology, such as complete metric spaces. We show that in many cases, researchers using these tools have derived conclusions that are incorrect, trivial, or limited.
We present an open-source tool for visualizing multi-head self-attention in Transformer-based language representation models. The tool extends earlier work by visualizing attention at three levels of granularity: the attention-head level, the model level, and the neuron level. We describe how each of these views can he…
The purpose of this thesis is to study classical combinatorial objects, such as polytopes, polytopal complexes, and subspace arrangements, using tools that have been developed in combinatorial topology, especially those tools developed in connection with (discrete) differential geometry, geometric group theory and low-…
Paper proposes a diagnostic tool for evaluating model performance out-of-sample.
Several recent papers in digital topology have sought to obtain fixed point results by mimicking the use of tools from classical topology, such as complete metric spaces and homotopy invariant fixed point theory. We show that in many cases, researchers using these tools have derived conclusions that are incorrect or tr…
Book covers tools for zeroth-order convex optimisation.
We develop two new tools for use in Alexandrov geometry: a theory of ramified orientable double covers and a particularly useful version of the Slice Theorem for actions of compact Lie groups. These tools are applied to the classification of compact, positively curved Alexandrov spaces with maximal symmetry rank.
Survey examines challenges and tools for integrating multiple types of omics data.
Parabolic mapping class acts on curve graphs of infinite type surfaces.
Recent work has shown that Field-Programmable Gate Arrays (FPGAs) play an important role in the acceleration of Machine Learning applications. Initial specification of machine learning applications are often done using a high-level Python-oriented framework such as Tensorflow, followed by a manual translation to either…
Browsing and finding relevant information for Bangladeshi laws is a challenge faced by all law students and researchers in Bangladesh, and by citizens who want to learn about any legal procedure. Some law archives in Bangladesh are digitized, but lack proper tools to organize the data meaningfully. We present a text vi…
Probabilistic models can handle causal inference without special tools.