When applied to question answering and other text generation tasks, language models (LMs) may be queried generatively (by sampling answers from their output distribution) or discriminatively (by...

Apply by May 26 if excited by

• High-throughput parallelism for **transparent** LLM inference
• Service autoscaling for public science*on NCSA HPC GPUs
• Robustness+monitoring for safe use
• A mission to unlock broad access to frontier AI research

http…

We introduce Xmodel-VLM, a cutting-edge multimodal vision language model. It is designed for efficient deployment on consumer GPU servers. Our work directly confronts a pivotal industry issue by...

Tired of MMLU? The current models already hit the ceiling? It's time to upgrade MMLU!

Introducing our new benchmark MMLU-Pro, a more robust and challenging massive multi-task language understanding benchmark with 12K questions.

What's New?
1. MMLU-Pro uses…

The computation necessary for training Transformer-based language models has skyrocketed in recent years. This trend has motivated research on efficient training algorithms designed to improve...

It's always exciting when a new paper with a LoRA-like method for efficient LLM finetuning comes out. In "MoRA: High-Rank Updating for Parameter-Efficient Finetuning (https://t.co/ieQ3uxWpqM)," the authors take a related yet opposite approach to low-rank…

Visual language models (VLMs) rapidly progressed with the recent success of large language models. There have been growing efforts on visual instruction tuning to extend the LLM with visual...

Past work has established scaling laws that predict the performance of a neural language model (LM) as a function of its parameter count and the number of tokens it's trained on, enabling optimal...

#humanoide #robots #robotics #ai #unitree

Join the discussion on this paper page

Leopold Aschenbrenner, June 2024 You can see the future first in San Francisco. Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added…