HF Spaces for demoing chat completion models—no ZeroGPU, WebGPU, or BYOK included. Thank you so much to these devs!
Urro PRO
urroxyz
AI & ML interests
computational linguistics major 🤖🔎🔠
i am autistic. if i come off rude, i probably didn't mean to. please feel free to ask me for clarification.
Recent Activity
liked a dataset about 6 hours ago
common-canvas/commoncatalog-cc-by liked a model about 12 hours ago
talkie-lm/talkie-1930-13b-it updated a collection 1 day ago
WTF GENIUS PAPERSOrganizations
Papers that made me appreciate my major and my life a little more. obs=Observation, innov=Innovation. Most papers are abt improving tiny models.
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Diffusion Language Models Know the Answer Before Decoding
Paper • 2508.19982 • Published • 27 -
ReFusion: A Diffusion Large Language Model with Parallel Autoregressive Decoding
Paper • 2512.13586 • Published • 93 -
LSRIF: Logic-Structured Reinforcement Learning for Instruction Following
Paper • 2601.06431 • Published • 12 -
Distribution-Aligned Sequence Distillation for Superior Long-CoT Reasoning
Paper • 2601.09088 • Published • 63
ONNX conversions of ASR models with attentions enabled for output. Especially useful for word-level timestamp extraction.
HF Spaces for demoing chat completion models—no ZeroGPU, WebGPU, or BYOK included. Thank you so much to these devs!
Papers that made me appreciate my major and my life a little more. obs=Observation, innov=Innovation. Most papers are abt improving tiny models.
-
Diffusion Language Models Know the Answer Before Decoding
Paper • 2508.19982 • Published • 27 -
ReFusion: A Diffusion Large Language Model with Parallel Autoregressive Decoding
Paper • 2512.13586 • Published • 93 -
LSRIF: Logic-Structured Reinforcement Learning for Instruction Following
Paper • 2601.06431 • Published • 12 -
Distribution-Aligned Sequence Distillation for Superior Long-CoT Reasoning
Paper • 2601.09088 • Published • 63
Datasets written by humans and/or reverse-engineered from text with deterministic algorithms. No illegal scraping or unethical synthesis *...mostly.
ONNX conversions of ASR models with attentions enabled for output. Especially useful for word-level timestamp extraction.