Tweet ; Neural networks AND NLP@Stanford
Common descendants
13 Documents
Omar Khattab sur X : "ColBERT in 81 languages by generalizing from English training! ..."
Tags:
2024-02-28 About
Omar Khattab sur X : "A thread on late interaction, how it works efficiently, and why/where it's been shown to improve quality"
Tags:
2024-02-05 About
Craig Macdonald sur X : "a thread of our main ColBERT research findings"
Tags:
2024-02-01 About
Jo Kristian Bergum sur X : (on "why using ColBERT?")
Tags:
2024-01-28 About
Omar Khattab sur X : "A🧵on beating the hardware lottery for retrieval: the internals of the late interaction stack. ColBERT..."
Tags:
2023-12-29 About
Zain Hasan sur X : "why do large language models pay more attention to and reason better over the beginning and end of what you tell them in prompts?"
Tags:
2023-11-19 About
Omar Khattab sur X : "This isn't the main point of this great new paper by @sophiaalthammer et al. But it's incredible how ColBERT at 1000 training queries is better than DPR trained at *50,000* queries!"
Tags:
2023-09-14 About
Daniel Vila Suero sur Twitter : "Data quality is key for LLMs, but we're building Open Source LLMs with data of "unknown" quality... Introducing Alpaca GarbageCollector..."
Tags:
2023-04-05 About
Omar Khattab sur Twitter : "New features in 𝗖𝗼𝗹𝗕𝗘𝗥𝗧 ‣ Index Updater. Simple API to add/remove documents..."
Tags:
2023-01-30 About
shikhar sur Twitter : "Instead of asking whether tree structure should be baked into NNs, our new paper asks if transformers already have a tendency to learn tree structured computations when trained on language, and if this structure is predictive of generalization! "
Tags:
2022-12-09 About
I.A.B sur Twitter : "When we "know the meaning" of a word, what is it that we know? For example, what does knowing the words "dolphin" and "tiger" entail?..."
Tags:
2022-04-15 About
Seth Stafford sur Twitter : "Here’s a nice paper (ICLR spotlight) on how to apply masking in LM training..."
Tags:
2021-10-16 About
Pablo Castro sur Twitter : "Random finding of the day for word embeddings: vec("apple")-vec("apples") yields a vector close to ipad, ipod, etc. (apples removes the "fruitness" from apple)
Tags:
2020-12-18 About