Croissant: A Metadata Format for ML-Ready Datasets
Paper
•
2403.19546
•
Published
•
1
Harvard University
university
Verified
AI & ML interests
Artificial General Intelligence (AGI), Artificial Superintelligence (ASI), Uplift, Apotheosis
Papers
Demystifying LLM-as-a-Judge: Analytically Tractable Model for Inference-Time Scaling
MRI Super-Resolution with Deep Learning: A Comprehensive Survey
skrishna
authored
2
papers
10 months ago
Post
2723
🔥🚀 Hey everyone! I'm excited to share my latest LLM release: Gilgamesh 72B, a model built on Qwen 2.5-72B Instruct. Gilgamesh was trained on a couple of my GammaCorpus datasets, specifically:
- rubenroy/GammaCorpus-CoT-Math-170k
- rubenroy/GammaCorpus-v2-5m
- rubenroy/GammaCorpus-Fact-QA-450k
I've submitted GGM 72B to the Open LLM Leaderboard for benchmarking, I'll send an update post once the results are in!
You can try it out and share your feedback, check out the model page and see what it can do:
👉 rubenroy/Gilgamesh-72B
Would love to hear your thoughts!
- rubenroy/GammaCorpus-CoT-Math-170k
- rubenroy/GammaCorpus-v2-5m
- rubenroy/GammaCorpus-Fact-QA-450k
I've submitted GGM 72B to the Open LLM Leaderboard for benchmarking, I'll send an update post once the results are in!
You can try it out and share your feedback, check out the model page and see what it can do:
👉 rubenroy/Gilgamesh-72B
Would love to hear your thoughts!
Post
2990
🎉 Fully released my newest models trained on my GammaCorpus dataset, Zurich 7B & 14B and Geneva 12B. Here is the model collections:
Zurich:
rubenroy/zurich-679b21284e207e2844bc025d
Geneva:
https://huggingface.co/collections/rubenroy/geneva-679e33a55d1576319b0d9cd4
If you would like to test them, feel free to visit their spaces:
rubenroy/Geneva-12B
rubenroy/Zurich-14B
rubenroy/Zurich-7B
Zurich:
rubenroy/zurich-679b21284e207e2844bc025d
Geneva:
https://huggingface.co/collections/rubenroy/geneva-679e33a55d1576319b0d9cd4
If you would like to test them, feel free to visit their spaces:
rubenroy/Geneva-12B
rubenroy/Zurich-14B
rubenroy/Zurich-7B
hlzhang109
authored
5
papers
about 1 year ago
Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark
Paper
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2304.03279
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Published
•
2
CoLoR-Filter: Conditional Loss Reduction Filtering for Targeted Language Model Pre-training
Paper
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2406.10670
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Published
•
4
DataComp-LM: In search of the next generation of training sets for language models
Paper
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2406.11794
•
Published
•
55
Eliminating Position Bias of Language Models: A Mechanistic Approach
Paper
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2407.01100
•
Published
•
8
Mind the Gap: Examining the Self-Improvement Capabilities of Large Language Models
Paper
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2412.02674
•
Published
skrishna
authored
10
papers
about 1 year ago
Are Large Language Models Post Hoc Explainers?
Paper
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2310.05797
•
Published
Post Hoc Explanations of Language Models Can Improve Language Models
Paper
•
2305.11426
•
Published
•
1
BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation
Paper
•
2101.11718
•
Published
Black-Box Access is Insufficient for Rigorous AI Audits
Paper
•
2401.14446
•
Published
•
3
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal
Paper
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2203.12574
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Published
TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations
Paper
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2207.04154
•
Published
Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten
Paper
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2302.04288
•
Published
Operationalizing a Threat Model for Red-Teaming Large Language Models (LLMs)
Paper
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2407.14937
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Published
•
1
Measuring Fairness of Text Classifiers via Prediction Sensitivity
Paper
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2203.08670
•
Published
Insights from the Inverse: Reconstructing LLM Training Goals Through Inverse RL
Paper
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2410.12491
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Published
•
4
skrishna
authored
a
paper
over 1 year ago