12 papers
Train Smarter, Not Longer: Memorization-Guided Data Reuse for Efficient LLM Training
Jingwei Zuo, Cong Zeng, Ilyas Chahed +6
The training paradigm of large language models has shifted from traditional one-pass training to multi-epoch training, as reasonable reuse of limited high-quality data can improve…
SigLino: Efficient Multi-Teacher Distillation for Agglomerative Vision Foundation Models
Sofian Chaybouti, Sanath Narayan, Yasser Dahou +6
Vision foundation models trained via multi-teacher distillation offer a promising path toward unified visual representations, yet the learning dynamics and data efficiency of such…
Are Arabic Benchmarks Reliable? QIMMA's Quality-First Approach to LLM Evaluation
Leen AlQadi, Ahmed Alzubaidi, Mohammed Alyafeai +6
We present QIMMA, a quality-assured Arabic LLM leaderboard that places systematic benchmark validation at its core. Rather than aggregating existing resources as-is, QIMMA applies…
ALRM: Agentic LLM for Robotic Manipulation
Vitor Gaboardi dos Santos, Ibrahim Khadraoui, Ibrahim Farhat +3
Large Language Models (LLMs) have recently empowered agentic frameworks to exhibit advanced reasoning and planning capabilities. However, their integration in robotic control pipel…
WavLink: Compact Audio-Text Embeddings with a Global Whisper Token
Gokul Karthik Kumar, Ludovick Lepauloux, Hakim Hacid
Whisper has become the de-facto encoder for extracting general-purpose audio features in large audio-language models, where a 30-second clip is typically represented by 1500 frame…
Competitive Audio-Language Models with Data-Efficient Single-Stage Training on Public Data
Gokul Karthik Kumar, Rishabh Saraf, Ludovick Lepauloux +3
Large language models (LLMs) have transformed NLP, yet their integration with audio remains underexplored despite audio's centrality to human communication. We introduce Falcon3-Au…