2025-01-29s

Reinforcement learning (RL) surpasses supervised fine-tuning (SFT) in fostering generalization in foundation models, while SFT aids RL’s stability; a comparative study across text and visual domains r…

Boosting Large Language Model (LLM) performance, researchers introduce Over-Tokenized Transformers, decoupling input/output vocabularies to improve language modeling. Scaling input vocabularies improv…

First-ever FP4 training framework for LLMs achieves accuracy comparable to BF16 and FP8, enabling efficient ultra-low precision training.

HISTOIRESMORALES: a new French dataset tackles the crucial issue of aligning language models with human moral values, providing valuable resources for ethical AI research in a previously underserved l…

DIFFSPLAT repurposes 2D image diffusion models to natively generate high-quality 3D Gaussian splats, overcoming limitations in existing 3D generation methods.

IndicMMLU-Pro: a new benchmark rigorously evaluates large language models’ multi-task language understanding capabilities across nine major Indian languages, pushing Indic language AI research forward…

Low-rank adapters combined with neural architecture search revolutionize LLM compression, enabling efficient fine-tuning and significantly reduced memory footprint.