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ORCIDArash Ahmadian
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2020 – today
- 2024
[j3]Amir Moslemi, Arash Ahmadian:
Subspace learning for feature selection via rank revealing QR factorization: Fast feature selection. Expert Syst. Appl. 256: 124919 (2024)- [c7]Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, Julia Kreutzer, Olivier Pietquin, Ahmet Üstün, Sara Hooker:
Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs. ACL (1) 2024: 12248-12267 - [c6]Aakanksha, Arash Ahmadian, Beyza Ermis, Seraphina Goldfarb-Tarrant, Julia Kreutzer, Marzieh Fadaee, Sara Hooker:
The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm. EMNLP 2024: 12027-12049 - [c5]John Dang, Arash Ahmadian, Kelly Marchisio, Julia Kreutzer, Ahmet Üstün, Sara Hooker:
RLHF Can Speak Many Languages: Unlocking Multilingual Preference Optimization for LLMs. EMNLP 2024: 13134-13156 - [c4]Yannis Flet-Berliac, Nathan Grinsztajn, Florian Strub, Eugene Choi, Bill Wu, Chris Cremer, Arash Ahmadian, Yash Chandak, Mohammad Gheshlaghi Azar, Olivier Pietquin, Matthieu Geist:
Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion. EMNLP 2024: 21353-21370 - [c3]Ted Zadouri, Ahmet Üstün, Arash Ahmadian, Beyza Ermis, Acyr Locatelli, Sara Hooker:
Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning. ICLR 2024 - [i12]Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, Julia Kreutzer, Olivier Pietquin, Ahmet Üstün, Sara Hooker:
Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs. CoRR abs/2402.14740 (2024) - [i11]Eugene Choi, Arash Ahmadian, Matthieu Geist, Olivier Pietquin, Mohammad Gheshlaghi Azar:
Self-Improving Robust Preference Optimization. CoRR abs/2406.01660 (2024) - [i10]Aakanksha, Arash Ahmadian, Beyza Ermis, Seraphina Goldfarb-Tarrant, Julia Kreutzer, Marzieh Fadaee, Sara Hooker:
The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm. CoRR abs/2406.18682 (2024) - [i9]Yannis Flet-Berliac, Nathan Grinsztajn, Florian Strub, Eugene Choi, Chris Cremer, Arash Ahmadian, Yash Chandak, Mohammad Gheshlaghi Azar, Olivier Pietquin, Matthieu Geist:
Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion. CoRR abs/2406.19185 (2024) - [i8]Nathan Grinsztajn, Yannis Flet-Berliac, Mohammad Gheshlaghi Azar, Florian Strub, Bill Wu, Eugene Choi, Chris Cremer, Arash Ahmadian, Yash Chandak, Olivier Pietquin, Matthieu Geist:
Averaging log-likelihoods in direct alignment. CoRR abs/2406.19188 (2024) - [i7]John Dang, Arash Ahmadian, Kelly Marchisio, Julia Kreutzer, Ahmet Üstün, Sara Hooker:
RLHF Can Speak Many Languages: Unlocking Multilingual Preference Optimization for LLMs. CoRR abs/2407.02552 (2024) - [i6]Aakanksha, Arash Ahmadian, Seraphina Goldfarb-Tarrant, Beyza Ermis, Marzieh Fadaee, Sara Hooker:
Mix Data or Merge Models? Optimizing for Diverse Multi-Task Learning. CoRR abs/2410.10801 (2024) - 2023
- [j2]Amir Moslemi
, Mahdi Bidar, Arash Ahmadian:
Subspace learning using structure learning and non-convex regularization: Hybrid technique with mushroom reproduction optimization in gene selection. Comput. Biol. Medicine 164: 107309 (2023) - [j1]Amir Moslemi, Arash Ahmadian:
Dual regularized subspace learning using adaptive graph learning and rank constraint: Unsupervised feature selection on gene expression microarray datasets. Comput. Biol. Medicine 167: 107659 (2023) - [c2]Arash Ahmadian, Louis S. P. Liu, Yue Fei, Konstantinos N. Plataniotis, Mahdi S. Hosseini:
Pseudo-Inverted Bottleneck Convolution for Darts Search Space. ICASSP 2023: 1-5 - [c1]Arash Ahmadian, Saurabh Dash, Hongyu Chen, Bharat Venkitesh, Stephen Zhen Gou, Phil Blunsom, Ahmet Üstün, Sara Hooker:
Intriguing Properties of Quantization at Scale. NeurIPS 2023 - [i5]Arash Ahmadian, Yue Fei, Louis S. P. Liu, Konstantinos N. Plataniotis, Mahdi S. Hosseini:
Pseudo-Inverted Bottleneck Convolution for DARTS Search Space. CoRR abs/2301.01286 (2023) - [i4]Arash Ahmadian, Saurabh Dash, Hongyu Chen, Bharat Venkitesh, Stephen Gou, Phil Blunsom, Ahmet Üstün, Sara Hooker:
Intriguing Properties of Quantization at Scale. CoRR abs/2305.19268 (2023) - [i3]Claas Voelcker, Arash Ahmadian, Romina Abachi, Igor Gilitschenski, Amir-massoud Farahmand:
λ-AC: Learning latent decision-aware models for reinforcement learning in continuous state-spaces. CoRR abs/2306.17366 (2023) - [i2]Ted Zadouri, Ahmet Üstün, Arash Ahmadian, Beyza Ermis, Acyr Locatelli, Sara Hooker:
Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning. CoRR abs/2309.05444 (2023) - 2022
- [i1]Amir Moslemi, Arash Ahmadian:
Subspace Learning for Feature Selection via Rank Revealing QR Factorization: Unsupervised and Hybrid Approaches with Non-negative Matrix Factorization and Evolutionary Algorithm. CoRR abs/2210.00418 (2022)
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