Shi Feng

Dikutip oleh

	Semua	Sejak 2020
Kutipan	3962	3775
indeks-h	18	18
indeks-i10	20	19

1400

700

350

1050

201620172018201920202021202220232024202516 13 35 118 250 418 578 1006 1367 151

Akses publik

Lihat semua

8 artikel

1 artikel

tersedia

tidak tersedia

Berdasarkan pada mandat pendanaan

Pengarang bersama

Eric WallaceUC BerkeleyEmail yang diverifikasi di berkeley.edu
Jordan Boyd-GraberFull Professor, University of MarylandEmail yang diverifikasi di umiacs.umd.edu
Sameer SinghProfessor, UC Irvine | CTO, Spiffy AIEmail yang diverifikasi di uci.edu
Tony Z. ZhaoStanford UniversityEmail yang diverifikasi di stanford.edu
Pedro RodriguezResearch Scientist, FacebookEmail yang diverifikasi di fb.com
Chenhao TanUniversity of ChicagoEmail yang diverifikasi di chenhaot.com
Mohit IyyerAssociate Professor, University of MarylandEmail yang diverifikasi di umd.edu
He HeNew York UniversityEmail yang diverifikasi di cs.nyu.edu
Matt GardnerScaled CognitionEmail yang diverifikasi di scaledcognition.com
Nikhil KandpalComputer Science Ph.D. Candidate, University of TorontoEmail yang diverifikasi di cs.toronto.edu
Alvin Grissom IIAssociate Professor, Haverford CollegeEmail yang diverifikasi di haverford.edu
Ming Zhou (周明)Chief Scientist at Sinovation, ACL president (2019), VP of CCF(2020-2024)Email yang diverifikasi di chuangxin.com
Shujie Liu (刘树杰）Microsoft Research AsiaEmail yang diverifikasi di microsoft.com
Chenglei SiStanford UniversityEmail yang diverifikasi di stanford.edu
Ikuya YamadaStudio Ousia, RIKENEmail yang diverifikasi di ousia.jp
Yiming ZhangCarnegie Mellon UniversityEmail yang diverifikasi di cs.cmu.edu
Shuo Ren (任烁)Institute of Automation Chinese Academy of SciencesEmail yang diverifikasi di ia.ac.cn
Chacha ChenUniversity of ChicagoEmail yang diverifikasi di uchicago.edu
Nitish JoshiNew York UniversityEmail yang diverifikasi di nyu.edu
Dan FriedmanPrinceton UniversityEmail yang diverifikasi di princeton.edu

Ikuti

Shi Feng

The George Washington University

Email yang diverifikasi di gwu.edu - Beranda

AI safety alignment


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Calibrate before use: Improving few-shot performance of language models Z Zhao, E Wallace, S Feng, D Klein, S Singh ICML 2021, 2021	1315	2021
Universal adversarial triggers for attacking and analyzing NLP E Wallace, S Feng, N Kandpal, M Gardner, S Singh EMNLP 2019, 2019	934	2019
Pathologies of Neural Models Make Interpretations Difficult S Feng, E Wallace, A Grissom II, M Iyyer, P Rodriguez, J Boyd-Graber EMNLP 2018, 2018	379	2018
Concealed data poisoning attacks on NLP models E Wallace, TZ Zhao, S Feng, S Singh NAACL 2021, 2020	194	2020
Trick me if you can: Human-in-the-loop generation of adversarial examples for question answering E Wallace, P Rodriguez, S Feng, I Yamada, J Boyd-Graber TACL 2019, 2019	189	2019
Active example selection for in-context learning Y Zhang, S Feng, C Tan EMNLP 2022, 2022	165	2022
What can AI do for me? evaluating machine learning interpretations in cooperative play S Feng, J Boyd-Graber IUI 2019, 2019	153	2019
Knowledge-based semantic embedding for machine translation C Shi, S Liu, S Ren, S Feng, M Li, M Zhou, X Sun, H Wang Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016	102	2016
LLM evaluators recognize and favor their own generations A Panickssery, SR Bowman, S Feng NeurIPS 2024, 2024	82	2024
Improving Attention Modeling with Implicit Distortion and Fertility for Machine Translation S Feng, S Liu, N Yang, M Li, M Zhou, KQ Zhu COLING, 2016	75*	2016
Interpreting neural networks with nearest neighbors E Wallace, S Feng, J Boyd-Graber BlackboxNLP @ EMNLP 2018, 2018	61	2018
Understanding impacts of high-order loss approximations and features in deep learning interpretation S Singla, E Wallace, S Feng, S Feizi ICML 2019, 2019	60	2019
Misleading failures of partial-input baselines S Feng, E Wallace, J Boyd-Graber ACL 2019, 2019	42	2019
Quizbowl: The case for incremental question answering P Rodriguez, S Feng, M Iyyer, H He, J Boyd-Graber arXiv preprint arXiv:1904.04792, 2019	41	2019
Machine explanations and human understanding C Chen, S Feng, A Sharma, C Tan TMLR 2023, 2022	33	2022
Measuring inductive biases of in-context learning with underspecified demonstrations C Si, D Friedman, N Joshi, S Feng, D Chen, H He ACL 2023, 2023	31	2023
Large Language Models Help Humans Verify Truthfulness--Except When They Are Convincingly Wrong C Si, N Goyal, ST Wu, C Zhao, S Feng, H Daumé III, J Boyd-Graber NAACL 2024, 2023	25	2023
Human-centered evaluation of explanations J Boyd-Graber, S Carton, S Feng, QV Liao, T Lombrozo, A Smith-Renner, ... NAACL 2022 Tutorial, 2022	23	2022
Human-computer question answering: The case for quizbowl J Boyd-Graber, S Feng, P Rodriguez The NIPS'17 Competition: Building Intelligent Systems, 169-180, 2018	13	2018
Language models learn to mislead humans via rlhf J Wen, R Zhong, A Khan, E Perez, J Steinhardt, M Huang, SR Bowman, ... arXiv preprint arXiv:2409.12822, 2024	12	2024

Sistem tidak dapat melakukan operasi ini. Coba lagi nanti.

Artikel 1–20

Kutipan per tahun

Kutipan duplikat

Kutipan yang digabung

Tambahkan pengarang bersamaPengarang bersama

Ikuti

Dikutip oleh

Pengarang bersama