In recent years, the advances in digitalisation have also adversely contributed to the significant rise in cybercrimes. Hence, building the threat intelligence to shield against rising cybercrimes has become a fundamental ...

For a finite group G, the size of a minimum generating set of G is denoted by d(G). Given a finite group G and an integer k, deciding if d(G)≤k is known as the minimum generating set (MIN-GEN) problem. A group G of order ...

The success of deep learning in supervised fine-grained recognition for domain-specific tasks relies heavily on expert annotations. The Open-Set for fine-grained Self-Supervised Learning (SSL) problem aims to enhance ...

The boxicity (cubicity) of an undirected graph Γ is the smallest non-negative integer k such that Γ can be represented as the intersection graph of axis-parallel rectangular boxes (unit cubes) in Rk. An undirected graph ...

Neural radiance fields (NeRF) have exhibited highly photorealistic rendering of novel views through per-scene optimization over a single 3D scene. With the growing popularity of NeRF and its variants, they have become ...

The rapid growth of digital communication has driven the widespread use of code-mixing, particularly Hindi-English, in multilingual communities. Existing datasets often focus on romanized text, have limited scope, or rely ...

One of the standard ways to study scenarios beyond the Standard Model involves extending the Higgs Sector. This work examines the Three Higgs Doublet Model (3HDM) in a Type-Z or democratic setup, where each Higgs doublet ...

Hardware accelerators such as GPUs are required for real-time, low-latency inference with Deep Neural Networks (DNN). However, due to the inherent limits to the parallelism they can exploit, DNNs often under-utilize the ...

Social media conversations unfold based on complex interactions between users, topics and time. While recent models have been proposed to capture network strengths between users, users' topical preferences and temporal ...

The rapid advancement of Large Language Models (LLMs) has intensified the need for evaluation frameworks that address the requirements of linguistically diverse regions, such as India, and go beyond English-centric benchmarks. ...