Παρακολούθηση
Han Guo
Han Guo
MIT
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα mit.edu - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
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RLPrompt: Optimizing Discrete Text Prompts With Reinforcement Learning
M Deng, J Wang, CP Hsieh, Y Wang, H Guo, T Shu, M Song, EP Xing, ...
arXiv preprint arXiv:2205.12548, 2022
3232022
VisualGPT: Data-efficient adaptation of pretrained language models for image captioning
J Chen, H Guo, K Yi, B Li, M Elhoseiny
arXiv preprint arXiv:2102.10407, 2021
2632021
Soft Layer-Specific Multi-Task Summarization with Entailment and Question Generation
H Guo, R Pasunuru, M Bansal
ACL 2018, 2018
1752018
Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits
H Guo, R Pasunuru, M Bansal
AAAI 2020, 2020
1432020
FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging
H Guo, NF Rajani, P Hase, M Bansal, C Xiong
arXiv preprint arXiv:2012.15781, 2020
1252020
Uncertainty toolbox: an open-source library for assessing, visualizing, and improving uncertainty quantification
Y Chung, I Char, H Guo, J Schneider, W Neiswanger
arXiv preprint arXiv:2109.10254, 2021
992021
Dynamic Multi-Level Multi-Task Learning for Sentence Simplification
H Guo, R Pasunuru, M Bansal
COLING 2018, 2018
922018
MPCFormer: fast, performant and private Transformer inference with MPC
D Li, R Shao, H Wang, H Guo, EP Xing, H Zhang
arXiv preprint arXiv:2211.01452, 2022
752022
Efficient (Soft) Q-Learning for Text Generation with Limited Good Data
H Guo, B Tan, Z Liu, E Xing, Z Hu
Findings of the Association for Computational Linguistics: EMNLP 2022, 6969-6991, 2022
60*2022
AutoSeM: Automatic Task Selection and Mixing in Multi-Task Learning
H Guo, R Pasunuru, M Bansal
NAACL 2019, 2019
572019
Towards Improving Abstractive Summarization via Entailment Generation
R Pasunuru, H Guo, M Bansal
Proceedings of the Workshop on New Frontiers in Summarization, 27-32, 2017
482017
LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning
H Guo, P Greengard, EP Xing, Y Kim
arXiv preprint arXiv:2311.12023, 2023
412023
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach
H Guo, P Greengard, H Wang, A Gelman, Y Kim, EP Xing
arXiv preprint arXiv:2302.04228, 2023
172023
An Overview of Uncertainty Calibration for Text Classification and the Role of Distillation
H Guo, R Pasunuru, M Bansal
Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP …, 2021
102021
Fast Matrix Multiplications for Lookup Table-Quantized LLMs
H Guo, W Brandon, R Cholakov, J Ragan-Kelley, EP Xing, Y Kim
arXiv preprint arXiv:2407.10960, 2024
82024
DORB: Dynamically Optimizing Multiple Rewards with Bandits
R Pasunuru, H Guo, M Bansal
Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020
72020
The Surprising Effectiveness of Test-Time Training for Abstract Reasoning
E Akyürek, M Damani, L Qiu, H Guo, Y Kim, J Andreas
arXiv preprint arXiv:2411.07279, 2024
62024
Training-Free Activation Sparsity in Large Language Models
J Liu, P Ponnusamy, T Cai, H Guo, Y Kim, B Athiwaratkun
arXiv preprint arXiv:2408.14690, 2024
42024
Pushing the Limits of Large Language Model Quantization via the Linearity Theorem
V Malinovskii, A Panferov, I Ilin, H Guo, P Richtárik, D Alistarh
arXiv preprint arXiv:2411.17525, 2024
22024
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