We're quite fond of our length-normalized direct alignment at Liquid (see https://
arxiv.org/abs/2511.23404)
@maximelabonne
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Liquid AI Introduces Length-Normalized Direct Alignment Method
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AgentTrove: New Agentic Dataset with 1.7M Samples Released
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AgentTrove: new agentic dataset with 1.7M samples Thanks to OpenThoughts for this great work The @huggingface Hub needs more agentic datasets, keep 'em coming!
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Tau3-Bench Timing Concerns Against Competing Models
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Not sure if this is a good look since most of the competing models were released BEFORE Tau3-Bench
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Pixtral Scaled-Up Model: Tradition Over Modern AI Approaches
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Reject modernity, embrace tradition (it's a scaled-up Pixtral)
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Embedding Layers in Small Models: Architecture and Training Optimization
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Did you know that the embedding layer can contain 63% of total model parameters? In this talk, I present unique challenges of small models from architecture (don't build giant embedding layers) to post-training (how to fix doom looping) ↓ Slides in the comments ↓
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LFM2-VL Language Model Deployed on Satellite Successfully
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This is so cool: LFM2-VL deployed directly on a satellite! Building HAL 9000 one step at a time.
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Liquid AI showcases at ICLR Rio with Mercedes partnership
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Rio was amazing, I had such a fun time at @iclr_conf @liquidai presented many papers, managed a busy booth, announced a partnership with Mercedes, and organized a (delicious) dinner event 10/10 would do it again!
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Tokenizer: The Real Business Model Behind AI Models
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The model might be the product, but the tokenizer is the business plan
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Anthropic’s Hidden 30% Cost Increase via Tokenizer Change
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Turns out Anthropic basically snuck in a 30% cost increase by changing the tokenizer