EdinburghNLP - Natural Language Processing Group at the University of Edinburgh

university

https://edinburghnlp.inf.ed.ac.uk/

AI & ML interests

We do research in all core areas of natural language processing, including morphology, parsing, semantics, discourse, language generation, and machine translation. EdinburghNLP also has a strong track record of work at the interface of NLP with other areas, including speech technology, machine learning, computer vision, cognitive modeling, social media, information retrieval, robotics, bioinformatics, and educational technology.

Recent Activity

pminervini authored a paper 1 day ago

FLARE: Faithful Logic-Aided Reasoning and Exploration

pminervini authored a paper 1 day ago

SynDARin: Synthesising Datasets for Automated Reasoning in Low-Resource Languages

pminervini authored a paper 1 day ago

Analysing the Residual Stream of Language Models Under Knowledge Conflicts

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EdinburghNLP's activity

pminervini

authored 6 papers 1 day ago

FLARE: Faithful Logic-Aided Reasoning and Exploration

Paper • 2410.11900 • Published Oct 14, 2024 • 3

SynDARin: Synthesising Datasets for Automated Reasoning in Low-Resource Languages

Paper • 2406.14425 • Published Jun 20, 2024 • 1

posted an update 7 days ago

Post

2941

🚀 Introducing @huggingface Open Deep-Research💥

In just 24 hours, we built an open-source agent that:
✅ Autonomously browse the web
✅ Search, scroll & extract info
✅ Download & manipulate files
✅ Run calculations on data

55% on GAIA validation set! Help us improve it!💡
https://huggingface.co/blog/open-deep-research

3 replies

albertvillanova

posted an update about 1 month ago

Post

2052

Discover all the improvements in the new version of Lighteval: https://huggingface.co/docs/lighteval/

tomhosking

authored a paper about 2 months ago

If You Can't Use Them, Recycle Them: Optimizing Merging at Scale Mitigates Performance Tradeoffs

Paper • 2412.04144 • Published Dec 5, 2024 • 4

albertvillanova

posted an update 3 months ago

Post

1777

🚨 How green is your model? 🌱 Introducing a new feature in the Comparator tool: Environmental Impact for responsible #LLM research!
👉 open-llm-leaderboard/comparator
Now, you can not only compare models by performance, but also by their environmental footprint!

🌍 The Comparator calculates CO₂ emissions during evaluation and shows key model characteristics: evaluation score, number of parameters, architecture, precision, type... 🛠️
Make informed decisions about your model's impact on the planet and join the movement towards greener AI!

albertvillanova

posted an update 3 months ago

Post

1584

🚀 New feature of the Comparator of the 🤗 Open LLM Leaderboard: now compare models with their base versions & derivatives (finetunes, adapters, etc.). Perfect for tracking how adjustments affect performance & seeing innovations in action. Dive deeper into the leaderboard!

🛠️ Here's how to use it:
1. Select your model from the leaderboard.
2. Load its model tree.
3. Choose any base & derived models (adapters, finetunes, merges, quantizations) for comparison.
4. Press Load.
See side-by-side performance metrics instantly!

Ready to dive in? 🏆 Try the 🤗 Open LLM Leaderboard Comparator now! See how models stack up against their base versions and derivatives to understand fine-tuning and other adjustments. Easier model analysis for better insights! Check it out here: open-llm-leaderboard/comparator 🌐

pminervini

authored a paper 3 months ago

Steering Knowledge Selection Behaviours in LLMs via SAE-Based Representation Engineering

Paper • 2410.15999 • Published Oct 21, 2024 • 19

albertvillanova

posted an update 4 months ago

Post

3165

🚀 Exciting update! You can now compare multiple models side-by-side with the Hugging Face Open LLM Comparator! 📊

open-llm-leaderboard/comparator

Dive into multi-model evaluations, pinpoint the best model for your needs, and explore insights across top open LLMs all in one place. Ready to level up your model comparison game?