This letter presents a nonlinear disturbance observer-parameterized control barrier function (DOp-CBF) designed for a robust safety control system under external disturbances. This framework emphasizes that the safety bounds are relevant to the distu...
We present some conditions for social preference transitivity under the majority rule when the individual preferences include cycles. First, our concern is with the restriction on the preference orderings of individuals except those (called cycle mem...
Time series prediction is often complicated by distribution shift which demands adaptive models to accommodate time-varying distributions. We frame time series prediction under distribution shift as a weighted empirical risk minimisation problem. The...
Using the most comprehensive source of commercially available data on the US National Market System, we analyze all quotes and trades associated with Dow 30 stocks in 2016 from the vantage point of a single and fixed frame of reference. We find that...
An opinionated OTP framework wrapper (⭐ 26)
We present a flexible statistical modelling framework to deal with multivariate count data along with longitudinal and repeated measures structures. The covariance structure for each response variable is defined in terms of a covariance link function...
We introduce a black-box interpretability framework that learns a verifiable constitution: a natural language summary of how changes to a prompt affect a model's specific behavior, such as its alignment, correctness, or adherence to constraints. Our...
Referring expression segmentation (RES) aims at segmenting the entities' masks that match the descriptive language expression. While traditional RES methods primarily address object-level grounding, real-world scenarios demand a more versatile framew...
The "pre-training then fine-tuning (FT)" paradigm is widely adopted to boost the model performance of deep learning-based methods for medical volumetric segmentation. However, conventional full FT incurs high computational and memory costs. Thus, it...
In the framework of research into radioactive waste disposal, this paper presents some tests carried out to investigate the effects of temperature on the changes in permeability of Boom between 20 and 90 deg C. Constant head permeability tests were c...
The rapidly evolving field of autonomous driving systems (ADSs) is full of promise. However, in order to fulfil these promises, ADSs need to be safe in all circumstances. This paper introduces ISS-Scenario, an autonomous driving testing framework in...
DSL and compiler framework for automated finite-differences and stencil computation (⭐ 672)
In machine learning (ML), the inference phase is the process of applying pre-trained models to new, unseen data with the objective of making predictions. During the inference phase, end-users interact with ML services to gain insights, recommendation...
Aug 25, 2025 · The “Father of Modern Branding” Brings New Views to Marketing Today The fundamentals of modern branding and brand-building can be captured in the intertwined 5Bs, …
Personal branding is often framed in marketing terms such as 'product,' 'added value,' and 'promise,' highlighting its parallels with product branding and
The rapid growth in user generated content on social media has resulted in a significant rise in demand for automated content moderation. Various methods and frameworks have been proposed for the tasks of hate speech detection and toxic comment class...
In this paper, we design a new polar slotted ALOHA (PSA) protocol over the slot erasure channels, which uses polar coding to construct the identical slot pattern (SP) assembles within each active user and base station. A theoretical analysis framewor...
Long context understanding remains challenging for large language models due to their limited context windows. This paper introduces Long Input Fine-Tuning (LIFT) for long context modeling, a novel framework that enhances LLM performance on long-cont...
Existing benchmarks for large multimodal models (LMMs) often fail to capture their performance in real-time, adversarial environments. We introduce LM Fight Arena (Large Model Fight Arena), a novel framework that evaluates LMMs by pitting them agains...
Design and optimization of higher efficiency, lower-emission internal combustion engines are highly dependent on fuel chemistry. Resolving chemistry for complex fuels, like gasoline, is challenging. A solution is to study a fuel surrogate: a blend of...