Pixel Aligned Language Models Proposes PixelLLM to equip LLMs... with localization capability proj: abs:show more

Automating the Search for Artificial Life with Foundation Models... Presents ASAL, the first use of vision-language models in Artificial Life, discovering diverse, novel simulations across substrates proj: abs:show more

Major AI breakthrough: Diffusion Large Language Models are here!... They're 10x faster and 10x cheaper than traditional LLMs. Here's everything you need to know:show more

starting the week with a true groundbreaking work 💥... Large Language Diffusion Models the first billion-parameter scale diffusion model competitive with its pairs (8B model comparable to LLaMA 3 8B) it gets rid of the michael scott syndrome on existing LLMsshow more

Text-To-4D Dynamic Scene Generation Presents MAV3D (Make-A-Video3D), a method... for generating three-dimensional dynamic scenes from text descriptions. proj: abs:show more

Wouldn’t it be nice if ChatGPT could find your... missing keys for you? Our latest research from Berkeley AI Research + Google AI suggests that robots can use large language models (LLMs) to find hidden objects faster. 🧵👇show more

🚨New paper! Generative models are often “miscalibrated”. We calibrate... diffusion models, LLMs, and more to meet desired distributional properties. E.g. we finetune protein models to better match the diversity of natural proteins.show more

Laika AI x Nuklai Excited to announce our partnership... with Nuklai Nuklai is an innovative data ecosystem that will fuel the next generation of AI and Large Language Models (LLMs). Together, we're revolutionizing on-chain data accessibility and monetization. By combining Laika AI's blockchain analytics with Nuklai's ecosystem, we're creating new opportunities for data utilization powered by $LKI.show more

Our latest language model, Hermes 4, is FREE through... the entire holiday weekend! Try an AI that's aligned to you.show more

I just created a technology to turn 3d models... into refined Pixel Art #unity3d #madewithunity #gamedev #IndieGameDev #indiedevelopershow more

🌍 Physical AI, Large Geospatial Models, and OVRMaps LLMs... understand language. But the next evolution of AI is about machines that can move, see, and operate in the physical world. This is Physical AI, and it’s already happening. 🧵👇🏼show more

Mastering Diverse Domains through World Models abs: project page:

All the big language models under one roof for... the very first time 🤯 Compare the output of OpenAI ChatGPT, Anthropic's Claude and Cohere's language model in a single playground!! Check out this amazing tool to get the best of large language models 👇show more

introducing: pixel art reveal for Framer turn any image... (doesn't have to be pixelated) into a pixel-by-pixel animation with full control over size, order, timing, and scroll triggers. comment “PIXEL” and i’ll send it to you!show more

Finishing 2024 with one more research result! We’ve trained... small language agents to do hard sci tasks: engineering proteins, manipulating DNA, and working with sci literature in a new library called Aviary. We beat humans and frontier LLMs on these tasks!show more

I think my large language models are malfunctioning

We found a new way to get language models... to reason. 🤯 No RL, no training, no verifiers, no prompting. ❌ With better sampling, base models can achieve single-shot reasoning on par with (or better than!) GRPO while avoiding its characteristic loss in generation diversity.show more

Language models predict the next token. Interactive video models... predict the next video frame. We're in the 2022-era of these models, but video feeling sentient is imminent, along with an explosion of applications.show more

Can Vision-Language Models Solve the Shell Game? paper:

LongWriter Unleashing 10,000+ Word Generation from Long Context LLMs... discuss: Current long context large language models (LLMs) can process inputs up to 100,000 tokens, yet struggle to generate outputs exceeding even a modest length of 2,000 words. Through controlled experiments, we find that the model's effective generation length is inherently bounded by the sample it has seen during supervised fine-tuning (SFT). In other words, their output limitation is due to the scarcity of long-output examples in existing SFT datasets. To address this, we introduce AgentWrite, an agent-based pipeline that decomposes ultra-long generation tasks into subtasks, enabling off-the-shelf LLMs to generate coherent outputs exceeding 20,000 words. Leveraging AgentWrite, we construct LongWriter-6k, a dataset containing 6,000 SFT data with output lengths ranging from 2k to 32k words. By incorporating this dataset into model training, we successfully scale the output length of existing models to over 10,000 words while maintaining output quality. We also develop LongBench-Write, a comprehensive benchmark for evaluating ultra-long generation capabilities. Our 9B parameter model, further improved through DPO, achieves state-of-the-art performance on this benchmark, surpassing even much larger proprietary models. In general, our work demonstrates that existing long context LLM already possesses the potential for a larger output window--all you need is data with extended output during model alignment to unlock this capability.show more

Let your wearable data "speak" for itself! Introducing SensorLM,... a family of sensor-language foundation models trained on ~60 million hours of data, enabling robust wearable data understanding with natural language. →show more