2 citations · 2 across the 10 of their papers we have counts for
11 papers
The Last Visible Pixel: Probing Fine-Scale Perception in Vision-Language Models
Lujun Li, Lama Sleem, Niccolo Gentile +4
Recent vision-language models (VLMs) excel at multimodal understanding and reasoning, yet their fine-grained visual perception remains underexplored. A natural extension of ``How m…
The Necessity of Setting Temperature in LLM-as-a-Judge
Lujun Li, Lama Sleem, Yangjie Xu +4
Large Language Models (LLMs) are increasingly used as automated judges, yet decoding temperature is often set by intuition rather than evidence. We run over one million large scale…
Agent Skill Framework: Perspectives on the Potential of Small to Medium Language Models in Industrial Environments
Yangjie Xu, Lujun Li, Lama Sleem +7
Skills are getting increasingly used in recent agentic frameworks, performing robustly with proprietary LLMs. Yet, their effectiveness for small and medium-sized open-source models…
Temporal-Spatial Tubelet Embedding for Cloud-Robust MSI Reconstruction using MSI-SAR Fusion: A Multi-Head Self-Attention Video Vision Transformer Approach
Yiqun Wang, Lujun Li, Meiru Yue +1
Cloud cover in multispectral imagery (MSI) significantly hinders early-season crop mapping by corrupting spectral information. Existing Vision Transformer(ViT)-based time-series re…
NegBLEURT Forest: Leveraging Inconsistencies for Detecting Jailbreak Attacks
Lama Sleem, Jerome Francois, Lujun Li +3
Jailbreak attacks designed to bypass safety mechanisms pose a serious threat by prompting LLMs to generate harmful or inappropriate content, despite alignment with ethical guidelin…
Do Large Language Models Grasp The Grammar? Evidence from Grammar-Book-Guided Probing in Luxembourgish
Lujun Li, Yewei Song, Lama Sleem +7
Grammar refers to the system of rules that governs the structural organization and the semantic relations among linguistic units such as sentences, phrases, and words within a give…
Uncovering Zero-Shot Generalization Gaps in Time-Series Foundation Models Using Real-World Videos
Lujun Li, Lama Sleem, Yiqun Wang +3
Recent research on time-series foundation models (TSFMs) has underscored the scarcity of real-world data, often supplemented with synthetic sources in existing datasets, whose gene…
Small Language Models in the Real World: Insights from Industrial Text Classification
Lujun Li, Lama Sleem, Niccolo' Gentile +2
With the emergence of ChatGPT, Transformer models have significantly advanced text classification and related tasks. Decoder-only models such as Llama exhibit strong performance an…
Exploring the Impact of Temperature on Large Language Models:Hot or Cold?
Lujun Li, Lama Sleem, Niccolo' Gentile +2
The sampling temperature, a critical hyperparameter in large language models (LLMs), modifies the logits before the softmax layer, thereby reshaping the distribution of output toke…
Vision Transformer-Based Time-Series Image Reconstruction for Cloud-Filling Applications
Lujun Li, Yiqun Wang, Radu State
Cloud cover in multispectral imagery (MSI) poses significant challenges for early season crop mapping, as it leads to missing or corrupted spectral information. Synthetic aperture…
Is Small Language Model the Silver Bullet to Low-Resource Languages Machine Translation?
Yewei Song, Lujun Li, Cedric Lothritz +6
Low-resource languages (LRLs) lack sufficient linguistic resources and are underrepresented in benchmark datasets, resulting in persistently lower translation quality than high-res…