1 citations · 1 across the 7 of their papers we have counts for
7 papers
TailLoR: Protecting Principal Components in Parameter-Efficient Continual Learning
Marius Dragoi, Ioana Pintilie, Alexandra Dragomir +2
Parameter-efficient finetuning methods based on spectral decomposition have enabled progress in Continual Learning. In this paper we introduce TailLoR, which utilizes the singular…
JumpLoRA: Sparse Adapters for Continual Learning in Large Language Models
Alexandra Dragomir, Ioana Pintilie, Antonio Barbalau +6
Adapter-based methods have become a cost-effective approach to continual learning (CL) for Large Language Models (LLMs), by sequentially learning a low-rank update matrix for each…
C-ing Clearly: Enhanced Binary Code Explanations using C code
Teodor Poncu, Ioana Pintilie, Marius Dragoi +2
Large Language Models (LLMs) typically excel at coding tasks involving high-level programming languages, as opposed to lower-level programming languages, such as assembly. We propo…
Beyond Pass@k: Breadth-Depth Metrics for Reasoning Boundaries
Marius Dragoi, Ioana Pintilie, Florin Gogianu +1
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a powerful paradigm to improve Large Language Models on reasoning tasks such as coding, math or logic. To asses…
ChronoGraph: A Real-World Graph-Based Multivariate Time Series Dataset
Adrian Catalin Lutu, Ioana Pintilie, Elena Burceanu +1
We present ChronoGraph, a graph-structured multivariate time series forecasting dataset built from real-world production microservices. Each node is a service that emits a multivar…
Electron transporting bilayers for perovskite solar cells: spray coating deposition of c-TiO2/m-SnO2-quantum dots
Anca G. Mirea, Ioana D. Vlaicu, Sarah Derbali +12
Herein we present a comparative study among different mesoporous electron transporter layers (ETLs), namely nanometric m-TiO2, m-SnO2 and m-SnO2 quantum dots (QDs), deposited by sp…
Time Series Anomaly Detection using Diffusion-based Models
Ioana Pintilie, Andrei Manolache, Florin Brad
Diffusion models have been recently used for anomaly detection (AD) in images. In this paper we investigate whether they can also be leveraged for AD on multivariate time series (M…