Stanford NLP Group

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Natural Language Processing/Machine Learning @chrmanning @jurafsky @percyliang @ChrisGPotts @tatsu_hashimoto @MonicaSLam @Diyi_Yang @YejinChoinka @StanfordAILab

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#	Date	Post	↓ Outlier	Views	Likes	Reposts	Bookmarks
1	Feb 12, '25	The final admission that the 2023 strategy of OpenAI, Anthropic, etc. (“simply scaling up model size, data, compute, and dollars spent will get us to AGI/ASI”) is no longer working	18.4×	311k	1.3k	110	405
2	Mar 25, '23	We’re not quite convinced that this sort of on-demand learning actually works to build a foundation in a subject …	16.4×	277k	606	66	255
3	Oct 25, '25	Today, we’re overjoyed to have a 25th Anniversary Reunion of @stanfordnlp. So happy to see so many of our former students back at @Stanford. And thanks to @StanfordHAI for the venu	16.1×	272k	311	40	31
4	May 6, '23	Is this the end of @Google/@DeepMind as leading presences at machine learning conferences? @JeffDean said: Things had to change. Google would take advantage of its own AI discoveri	14.2×	239k	216	53	85
5	Sep 21, '23	A 2023 update of the CS224N Natural Language Processing with Deep Learning YouTube playlist is now available with new lectures on pretrained models, prompting, RLHF, natural langua	12.7×	214k	1.1k	263	639
6	Apr 19, '25	Want to learn the engineering details of building state-of-the-art Large Language Models (LLMs)? Not finding much info in @OpenAI’s non-technical reports? @percyliang and @tatsu_ha	12×	203k	1.1k	158	1.3k
7	Jul 17, '19	Our new-ish, neural, pure Python stanfordnlp package provides grammatical analyses of sentences in over 50 human languages! Version 0.2.0 brought sensibly small model sizes and an	11.3×	0	1.8k	653	192
8	Mar 28, '19	CS224N Natural Language Processing with Deep Learning 2019 @Stanford course videos by @chrmanning, @abigail_e_see & guests are now mostly available (16 of 20). Big update from	11.1×	0	1.8k	607	230
9	Jan 30, '19	Out now: our new Python #NLProc package. StanfordNLP provides native, neural (PyTorch) tokenization, POS tagging and dependency parsing for 53 languages based on UD v2—and a Python	10.8×	0	1.7k	712	126
10	Aug 28, '23	It’s the origin of attention! @DBahdanau & @kchonyc couldn’t afford Google’s large multi-GPU neural MT, so they thought of a better way. Us either. @lmthang & @chrmanning i	10×	170k	336	65	108
11	Jan 5, '19	We’re gearing up for the 2019 edition of Stanford CS224N: Natural Language Processing with Deep Learning. Starts Jan 8—over 500 students enrolled—using PyTorch—new Neural MT assign	8.1×	0	1.5k	383	126
12	Sep 8, '19	Yes, @GoogleAI (well, all of @AlphabetINC) produces a lot of awesome AI research, but @Stanford + @MIT together produce more (judging by @NeurIPSConf papers!), and @Stanford + @MIT	4.9×	0	878	245	50
13	Feb 5, '23	Stanford Researcher ⁦@simran_s_arora⁩ develops a simple prompting strategy that enables open-source LLMs with 30x fewer parameters to exceed the few-shot performance of GPT3-175B -	4.8×	82k	404	71	195
14	Jan 15, '24	DPO (Direct Preference Optimization, ) now completely owns top-of-leaderboard medium-sized neural language models! (More experimentation with IPO, KTO, PPO, etc. would be great! –	4.5×	76k	496	94	243
15	Mar 8, '25	An introductory talk by Christopher Manning @chrmanning on “Large Language Models in 2025 – How much understanding and intelligence?” at the Workshop on a Public AI Assistant to Wo	4.4×	74k	828	156	647
16	Mar 17, '20	Announcing Stanza v1.0.0, the new packaging of our Python #NLProc library for many human languages (now including mainland Chinese), greatly improved and including NER. Documentati	4.1×	0	616	247	86
17	May 20, '18	Delete, Retrieve, Generate: A simple approach to doing neural style transfer on text, altering text for sentiment or style—Juncen Li, Robin Jia, He He & @percyliang #NAACL2018	4.1×	0	693	227	75
18	Jan 11, '24	There is a lovely, warm, and enthusiastic writeup of Direct Preference Optimization (DPO) by @rm_rafailov, @archit_sharma97, and @ericmitchellai from @NeurIPSConf 2023, leading thi	4.0×	68k	231	47	123
19	Jan 4, '20	Stanford CS224N: Natural Language Processing with Deep Learning is back for 2020, starting Jan 7, with over 500 students enrolled: #cs224n	4.0×	0	754	159	92
20	Oct 15, '25	😆	3.7×	63k	296	6	69
21	Mar 15, '25	“Look ma, no RL!” @tatsu_hashimoto gave a great talk at the @StanfordAILab faculty lunch on Friday 2025-03-14 on his work exploring the simplest way to achieve o1/R1-like test-time	3.3×	56k	529	53	314
22	Sep 8, '19	“Google & DeepMind have hired 23 professors, Amazon 17, Microsoft 13, and Uber, Nvidia & Facebook 7 each. Tech companies disagree that they are plundering academia. A Googl	3.3×	0	519	202	40
23	Aug 14, '17	Free, up-to-date @Stanford deep learning lectures: #NLProc & Vision	3.2×	0	517	236	12
24	Nov 1, '23	We still see lots of links to old releases of CS224N. Make sure you're getting the latest goodness (RLHF, prompting, transformers) from the 2023 release! YouTube: Website: For fee	3.1×	53k	299	78	190
25	Jul 24, '19	Good places for viewing “progress” in #NLProc—or at least the latest over-tuning results on various benchmarks😉: ☆ ☆ ☆ ☆ ☆ ☆	3.1×	0	452	188	79
26	Aug 22, '18	People usually get information from others in a multi-turn conversation. To approach this, we’ve released CoQA 🍃—A Conversational Question Answering Challenge by @sivareddyg•@danq	3.0×	0	438	206	32
27	Apr 3, '17	Stanford Lecture Collection—Natural Language Processing with Deep Learning—Manning/Socher	2.9×	0	485	221	2
28	Mar 8, '17	Lecture notes for Stanford CS224N Natural Language Processing with Deep Learning are now on GitHub. Edits welcome!	2.9×	0	454	230	1
29	Apr 8, '24	After a meteoric rise, DSPy is now the @stanfordnlp repository with the most GitHub stars. Big congratulations to @lateinteraction and his “team”. DSPy: Programming—not prompting—F	2.9×	49k	345	47	107
30	Aug 9, '22	Transformers just munched up another sub-area of Deep Learning! 😋 HT @HannesStaerk	2.9×	0	437	88	146
31	Oct 11, '18	Our free online lecture series on #NLProc: NLP by @jurafsky & @chrmanning (2012 Coursera nlp-class) —missing from web for ages for tedious reasons but now back! ❦ NLP with Deep	2.9×	0	442	179	48
32	Nov 10, '17	Pytorch implementations of many of the deep learning NLP models discussed in cs224n by Kim SungDong. #dlearn #NLProc	2.8×	0	506	190	2
33	Jun 3, '20	“Stanford has another fantastic NLP course which is also freely available online taught by a world renowned NLP researcher, academic, and author. The course in is From Languages to	2.8×	0	427	133	96
34	Nov 19, '18	“One thing I don’t like about the reporting around AI is that journalists seem to think the progress is happening in companies, and that’s not true. They are part of it, but a lot	2.7×	0	468	180	18
35	Dec 14, '17	Deep Learning, Language and Cognition: Video of an introductory talk on computational linguistics for a broad audience—from hand-written rules to modern neural net models—by Christ	2.7×	0	449	203	5
36	Jun 21, '18	How can you teach a machine learning system with human language rather than “labels”? With a semantic parser & labeling functions! New #ACL2018 paper by @bradenjhancock @paroma	2.7×	0	419	186	38
37	Jul 22, '19	Want to learn Natural Language Processing with Deep Learning a.k.a. Artificial Neural Network methods? Stanford’s @SCPD_AI is launching an online professional version of our #cs224	2.7×	0	443	122	73
38	Sep 1, '18	NLP with Deep Learning Course videos (from 2017): – corresponding materials:	2.6×	0	394	132	77
39	Apr 4, '18	Final project reports for CS224N: Natural Processing with Deep Learning are up. Lots of amazing work! Incredible students.	2.5×	0	396	148	38
40	Oct 26, '19	“[BERT] is the single biggest positive change we’ve had [to ⁦@Google⁩ search rankings] in the last five years,” ⁦@PanduNayak⁩ said. #nlproc Google Search Now Reads at a Higher Leve	2.4×	0	450	120	39
41	Jun 9, '22	Like we said, the author list of the foundation models paper is completely reasonable…	2.3×	0	438	52	62
42	Nov 23, '17	Some day deep learning might be a science. For now, it remains a craft, so people are rewarded for honing their skills at the craft. #dlearn	2.2×	0	365	150	0
43	Apr 26, '25	Our warmest congratulations to ⁦@danqi_chen⁩, ⁦@stanfordnlp⁩ grad and now Associate Professor at ⁦@PrincetonCS⁩ and Associate Director of ⁦@PrincetonPLI⁩ on her stunning ⁦⁦@iclr_co	2.2×	37k	274	20	14
44	Jan 4, '19	Geoff Hinton on importance of university research—“One worry is that the most fertile source of genuinely new ideas is graduate students being well advised in a university. They ha	2.2×	0	367	142	16
45	Sep 12, '18	Dependency trees are still useful for relation extraction, even in the neural age! Graph Convolution over Pruned Dependency Trees Improves Relation Extraction by @yuhaozhangx @qi2p	2.2×	0	366	120	30
46	Apr 27, '24	This weekend, we’re Natural Lake Processing! #NLProc	2.1×	36k	297	12	16
47	Jan 1, '19	10 Open-Sourced AI Datasets—SyncedReview 2018 In Review. 3/10 from ⁦@stanfordnlp⁩, 4/10 from ⁦@Stanford⁩. Open Images V4—MURA—BDD100K—SQuAD 2.0—CoQA—Spider 1.0—HotpotQA—Tencent ML	2.0×	0	321	136	29
48	Dec 14, '18	Congratulations to @danqi_chen on completing her dissertation on Neural Reading Comprehension and Beyond. She starts next year as an Asst Prof at @PrincetonCS: . But first, vacatio	2.0×	0	473	56	22
49	Jan 1, '24	A new winner on the @huggingface Open LLM Leaderboard at the end of December … combining the goodness of SOLAR-10.7B and Direct Preference Optimization (DPO)	2.0×	34k	169	34	73
50	Jul 31, '20	5 NLP Libraries Everyone Should Know \| by Pawan Jain \| Jul, 2020 \| Towards Data Science: spaCy, NLTK, Transformers, Gensim, and Stanza	2.0×	0	272	97	78
51	Jun 12, '18	Since 2016, SQuAD has been the key textual question answering benchmark, used by top AI groups & featured in AI Index——Today @pranavrajpurkar, Robin Jia & @percyliang relea	1.9×	0	289	122	18
52	Apr 25, '25	Even @chrmanning got in on the poster presentation action at @iclrconf	1.9×	32k	321	9	15
53	Aug 14, '24	.@stanfordnlp awards at #ACL2024 ▸ Best paper award @JulieKallini et al ▸ Outstanding paper award @aryaman2020 et al ▸ Outstanding paper award @shi_weiyan et al ▸ Best societal imp	1.9×	31k	324	37	31
54	May 21, '24	For this week’s NLP Seminar, we are thrilled to host @_jasonwei to talk about "Successful evals for large language models"! When: 05/23 Thurs 11am PT Non-Stanford affiliates regist	1.8×	31k	233	31	113
55	Feb 4, '19	Here’s a useful mixed tutorial and review of our newly introduced stanfordnlp Python #NLProc library built on PyTorch – – from Analytics Vidhya	1.8×	0	295	107	31
56	Sep 29, '25	Hi everyone! We're looking forward to the first NLP Seminar of the year! For this week's seminar, we are excited to host Tong Chen (@tomchen0) from University of Washington! If you	1.7×	30k	230	32	114
57	Jan 28, '19	We’ve released a new Visual Question Answering dataset to drive progress on real-image relational/compositional visual and linguistic understanding: GQA Questions, answers, images,	1.7×	0	268	108	18
58	Mar 8, '20	ELECTRA’s Replaced Token Detection pre-training is not only more compute efficient but gives a new best single model result on SQuAD v2 benchmark! 6 Mar 2020 ELECTRA: 88.716 EM 91.	1.7×	0	302	69	39
59	Nov 12, '24	Great article about our newest @stanfordnlp faculty member @Diyi_Yang in @Stanford Report: “I am passionate about developing a future where humans and AIs can collaborate to achiev	1.6×	27k	221	35	27
60	Dec 1, '19	Natural Language Inference (NLI) over tables by @WilliamWangNLP et al. Tables are a ubiquitous but little studied human information source stuck between text and structured data—th	1.6×	0	240	95	37
61	Apr 4, '25	Look who we found hanging out in her new @StanfordEng Gates Computer Science office! We’re truly delighted to welcome @YejinChoinka as a new @stanfordnlp faculty member, starting f	1.6×	26k	370	23	12
62	Apr 19, '25	Videos: Course website: Thx to @StanfordOnline	1.6×	26k	208	33	323
63	Oct 27, '19	How can computers answer questions with multi-step information needs? How can it be done efficiently and interpretably? @qi2peng2 and colleagues explain at #emnlp2019. Paper: Blog	1.5×	0	226	84	47
64	Feb 27, '19	Some people say that no one reads PhD dissertations any more. But (literally!) thousands of people wanted a copy of ⁦@danqi_chen’s recent dissertation, Neural Reading Comprehension	1.5×	0	292	70	23
65	Jan 10, '21	Stanford CS224N Natural Language Processing with Deep Learning is gearing up for its 2021 edition—starting Tue Jan 12, 4:30 Pacific for enrolled students. New lectures—transformers	1.5×	0	275	47	49
66	Dec 29, '18	Rasa open source chatbot API: Enterprises & customers want AI assistants, not FAQ chatbots, but they’re difficult to build; Since Google demoed Duplex, every developer, product	1.5×	0	250	87	27
67	Apr 10, '17	All lectures & materials for CS224N: NLP with Deep Learning by @chrmanning & @RichardSocher:	1.5×	0	246	110	0
68	Feb 14, '25	Congratulations to @stanfordnlp founder @chrmanning for being elected to The National Academy of Engineering (NAE, @theNASEM) Class of 2025 for the development and dissemination of	1.5×	25k	300	33	9
69	Sep 28, '19	On the importance of good, appropriate data sets for #NLProc, but how “the system” tends to wrongly incentivize researchers.	1.5×	0	220	85	24
70	Aug 17, '15	All slides from Montreal Deep Learning Summer School available at . 9 hours of #nlproc, 3 by @chrmanning #dlearn	1.5×	0	212	128	0
71	Jan 13, '19	Implementing a Natural Language Classifier in iOS Swift, which runs fully on device, with Keras + Core ML	1.4×	0	220	80	36
72	Oct 7, '25	Hi everyone! This Thursday, we will host the second NLP Seminar of the year! For this week's seminar, we are excited to host Tianyu Gao (@gaotianyu1350) from OpenAI and UC San Dieg	1.4×	24k	221	30	83
73	Jul 1, '20	In case you haven’t heard, the new unit for measuring computation runtime is TPU core years. But, if you missed that memo, since the numbers are already in the hundreds, you may as	1.4×	0	243	69	18
74	Apr 21, '20	We’ve just released Stanford CoreNLP v4.0.0, a new version of our widely used Java #NLProc package, after a long gap! Some big changes—i.e., compatibility problems but great for th	1.3×	0	241	67	16
75	Aug 29, '17	Do neural reading comprehension systems really understand? Robin Jia & Percy Liang’s @emnlp2017 paper suggests “No”	1.3×	0	190	97	0
76	Nov 25, '18	.@GoogleAI’s BERT unleashed a new performance level on SQuAD 2.0 QA —top 7 systems now all use it and are 2%+ above non-BERT systems. Scores equal summer 2017 SQuAD 1.0 scores. But	1.2×	0	237	66	12
77	Jun 19, '16	Just out: SQuAD—a 100,000+ question reading comprehension dataset—real text, Qs; leaderboard	1.2×	0	167	108	0
78	Feb 20, '19	Here’s another intro tutorial on using our new Python stanfordnlp package by @angelsalamanca –	1.2×	0	209	60	35
79	Oct 25, '21	Not only is @huggingface now hosting all our 🪶Stanza models (via @github LFS)—more reliable than our old fileserver, thx!—but thanks to work by @mervenoyann, 🤗🙏 you can now try	1.2×	0	222	51	26
80	Sep 25, '18	Cross-View Training—A semi-supervised learning technique by @clark_kev @lmthang Quoc Le @chrmanning at #emnlp2018. Allows training for your #NLProc task on large-scale unannotated	1.2×	0	183	67	24
81	Jul 28, '25	Big congratulations to @sewon__min on winning the inaugural ACL Computational Linguistics Dissertation Award at @aclmeeting 2025! #NLProc	1.2×	20k	278	27	9
82	Oct 23, '17	Non-convex optimization keeps looking easier and easier….	1.1×	0	208	77	0
83	Jun 23, '19	This is very nice work! (Though in full disclosure, we should note that @ethayarajh is turning up at Stanford in the Fall.)	1.1×	0	219	45	23
84	Jan 7, '20	.@stanfordnlp people’s #ICLR2020 papers #2—ELECTRA: @clark_kev and colleagues (incl. at @GoogleAI) show how to build a much more compute/energy efficient discriminative pre-trainer	1.1×	0	172	59	28
85	Jan 12, '21	We’re very excited to kick off our 2021 Stanford NLP Seminar series with Ian Tenney (@iftenney) of Google Research presenting on “BERTology and Beyond”! Thursday 10am PT. Open to t	1.1×	0	177	44	38
86	Aug 2, '19	What Does BERT Look At? An Analysis of BERT's Attention. Kevin Clark @clark_kev, Urvashi Khandelwal @ukhndlwl, Omer Levy @omerlevy_, Christopher D. Manning @chrmanning.	1.1×	0	184	54	28
87	Jan 9, '20	tf.keras in ⁦@TensorFlow⁩ 2.1 adds TextVectorization layer to flexibly map raw strings to tokens/word pieces/ngrams/vocab. An image is just a matrix of numbers but text always need	1.1×	0	195	59	17
88	May 15, '18	There is increasing convergence between this decade’s neural models and last decade’s probabilistic graphical models…	1.1×	0	204	60	10
89	Jan 29, '21	🆕 We've released Stanza v1.2—our Python neural NLP toolkit for PoS, parsing, NER for dozens of human languages. UD 2.7 models, multi-document support, faster tokenization, fix rac	1.1×	0	174	62	21
90	Mar 3, '18	An introduction to Visual Question Answering, with good discussion of the limitations of some of the current datasets.	1.1×	0	173	76	7
91	Apr 3, '19	What’s new in @Stanford CS224N Natural Language Processing with Deep Learning for 2019? Question answering—1D CNNs—subword models—contextual word representations—transformers—gener	1.0×	0	199	50	15
92	Apr 27, '18	You know how to do NLP. But do you consider fairness and ethical implications in your #NLProc research? Learn the latest on Socially Responsible NLP from Yulia Tsvetkov, Vinod Prab	1.0×	0	172	68	7
93	Nov 1, '21	Looking for a series to binge-watch with more depth? We are delighted to make available the latest CS224N: Natural Language Processing with Deep Learning. New content on transforme	1.0×	0	167	38	39
94	Jun 22, '18	GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations—learning a dependency graph to do deep transfer learning. Jake Zhao: “Perhaps this can also be seen	1.0×	0	173	53	16
95	Apr 2, '25	.@percyliang & @tatsu_hashimoto start the 2nd offering of CS336 Language Modeling from Scratch at @stanfordnlp. The class philosophy is Understanding by Building. We need many	1.0×	17k	237	33	109
96	Sep 6, '20	Wonderful to see some theory behind the great success of self-supervised learning. Still trying to get our slow brains around how strong the results are. Cameo for the Stanford Sen	1.0×	0	168	33	38
97	Mar 4, '17	Complete code for a starter neural chatbot from @chipro’s CS20SI @Stanford class on TensorFlow for Deep Learning	1.0×	0	169	66	0
98	Jan 8, '25	For this week’s NLP Seminar, we are thrilled to host @taoyds to give a talk titled From Vision-Language Models to Computer Use Agents: Data, Methods, and Evaluation! When: 1/9 Thur	0.9×	15k	165	30	54
99	Jan 6, '20	.@stanfordnlp people’s #ICLR2020 papers #1—@ukhndlwl and colleagues (incl. at @facebookai) show the power of neural nets learning a context similarity function for kNN in LM predic	0.9×	0	170	40	17
100	Feb 26, '20	It’s the 10th anniversary of @stanfordnlp on @Twitter, and approximately the 20th anniversary of the Stanford NLP Group and to celebrate … well, actually that's all coincidental, b	0.9×	0	201	28	1

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