text stringlengths 1 1k ⌀ | title stringclasses 230
values |
|---|---|
import alpaca_trade_api as tradeapi
def execute_trade ( action , num_shares , ticker , api_key , api_secret
, access_token , access_token_secret ):
api = tradeapi . REST ( api_key , api_secret ,
access_token , api_version = ’v2 ’)
if action == ’buy ’:
order = api . submit_order (
symbol = ticker ,
qty = num_share... | CAMEL- Communicative Agents for “Mind” Exploration of Large Scale Language Model Society |
(Al Kharaitiyat SC, club, Alaa Abdul-Zahra), (Al Khor, ground, Al Kharaitiyat SC), (Shabab Al-Ordon Club,
club, Alaa Abdul-Zahra) (Amar Osim, manager, Al Kharaitiyat SC)
Al Kharaitiyat SC are managed by Amar Osim and play at their ground at Al Khor. Al Kharaitiyat SC are also
the club for which Alaa Abdul-Zahra is a pl... | Prefix-Tuning |
Natural language generation:
(1) Summarization: Bang et al. [5] / Liang et al. [107] / Pu and Demberg [149] / Qin et al. [150]
(2) Dialogue: Bang et al. [5] / Lin and Chen [112] / Qin et al. [150] / Zheng et al. [245]
(3) Translation: Bang et al. [5] / Lyu et al. [121] / Wang et al. [196]
(4) Question answering: Bai et... | ASurveyonEvaluationofLargeLanguageModels |
[31] Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu,
Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. Lora:
Low-rank adaptation of large language models. arXiv preprint
arXiv:2106.09685, 2021. 2
[32] Lianghua Huang, Di Chen, Yu Liu, Shen Yujun, Deli Zhao,
and Zhou Jingren. Composer: Creative and controlla... | AddingConditionalControltoText-to-ImageDiffusionModels |
from the helpfulness data, rather than measuring how close it gets towards harmlessness data in particular.
In this way, we do not depend on the specific harmful content we have at hand, and can potentially filter
different kinds of non-helpfulness content.
To detect whether an input comes from the in-distribution (the h... | Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback |
takedowns;
https://doi.org/10.1017/9781108890960 Published online by Cambridge University Press
Democratic Transparency in the Platform Society
295
transparency regimes; self-transparency around advertising and content
moderation; and third-party tools, investigations, and audits. | Social_Media_and_Democracy |
Revisiting the road map of realistic human digitization,
the first step to tackling the above problem is building a
high-quality 3D biped cartoon characters dataset. We thus
introduce 3DBiCar, the first large-scale publicly available
3D biped cartoon character dataset following three criteria:
1) Diversity. 3DBiCar spa... | RaBit- Parametric Modeling of 3D Biped Cartoon Characters with a Topological-consistent Dataset |
Llama-2-7B-chat; SExt-Mistral-7B-ins-0.1 vs. Mistral-
7B-ins-0.1(w/SWA); SExt-SOLAR-10.5B-instruct-v1.0 vs.
SOLAR-10.5B-instruct-v1.0). On several datasets, Self-
Extend does not obtain performance improvement, such as
MultiNews. We think it’s mainly due to the length of such
datasets is not that long, for example, Mul... | Self-Extend LLM |
2.5.2 Tool-oriented Learning
Tool-oriented learning aims to make sequential decisions and execute tools to address complex tasks. As noted
by Yang et al. (2023a), while existing sequential decision-making methods have demonstrated impressive
proficiency in certain domains (Mnih et al., 2013; Shi et al., 2017; Akkaya et ... | Tool Learning with Foundation Models |
REGISTERED MODELS AND ML PRODUCTION
Production models have undergone the experimentation
phase and are then deployed in real-world applications. They
are typically used to make predictions or decisions based on
new data. Registering a model is the process of recording and
storing metadata about a trained model in a... | databrick 2023 report |
ACM Comput. Surv., Vol. 1, No. 1, Article . Publication date: February 2022.
Question: What is on thephone screen? Answer: A textmessage from a friend. Question: What can you seeout the window? Answer: Aparking lot. Question: Whom is the persontexting? Answer: The driver. 36
Ziwei Ji, et al. | SurveyofHallucinationinNatural Language Generation |
B. Comparison with Reflectance Reconstruc-
tion Methods
In Fig. 4, we have shown examples of rendered recon-
structions by our method, as well as two related methods,
namely AlbedoMM [61] and AvatarMe++ [42], both of
which recover reflectance from singe images, similarly to
our method. Here, we extend this comparison b... | Relightify-Relightable3DFacesfromaSingleImageviaDiffusionModels |
False or False )( False or False or False )( False or False )( False )PaLM 540B outputFlan-PaLM 540B outputQ: In the following sentences, explain the antecedent of the pronoun (which thing the pronoun refers to), or state that it is ambiguous.Sentence: The reporter and the chef will discuss their favorite dishes.Option... | Scaling Instruction-Finetuned Language Models |
● Better prompts.49 The way that a question is phrased can significantly affect a frontier
AI system’s response. For example, encouraging a model to think through its answer
“step by step” significantly improves performance on maths and logic problems.50
● Better tools. Frontier AI models can be trained to use t... | Capabilities and risks from frontier AI |
Asian
international
western
chinese
japanese
best
european
foreign
eastern
secondary
dietary
open
grand
vietnamese
russian
Hispanic
likely
african
american
mexican
united
cervical
spanish
potential
better
medical
more
new
educational
young
Table 12: Top 15 most biased adjectives/adverbs for each demographic
White
-0... | The Pile- An 800GB Dataset of Diverse Text for Language Modeling |
ex
ex+(cid:15)
sigmoid(cx)
linear
Figure 8: Problem Setting. Left: Data points (i-th sample x[i] and its augmented version x[i(cid:48)],
j-th sample x[j]) are sent to networks with weights θ, to yield outputs z[i], z[i(cid:48)] and z[j]. From the
outputs z, we compute pairwise squared distance d2
ij between z[i] and z... | A Cookbook of Self-Supervised Learning |
[72] Astrid Schepman and Paul Rodway. 2020. Initial validation of the general attitudes towards Artificial Intelligence Scale. Computers in
Human Behavior Reports 1 (2020), 100014. https://doi.org/10.1016/j.chbr.2020.100014
[73] Albrecht Schmidt. 2017. Augmenting human intellect and amplifying perception and cognitio... | Society’sAttitudesTowardsHumanAugmentation |
Figure 2 This figure shows BBQ bias scores, with larger scores indicating more bias. Claude models are significantly
less biased than the helpful-only model, which was trained without interventions for harms.
Furthermore, we report accuracy in the disambiguated context condition in Figure 3. We find that the accuracy
... | ClaudeModels |
Platforms also disclose takedown information to the European Commission
for inclusion in the Commission’s reporting on the Hate Speech Code of
Conduct (European Commission 2016, 2017). Under the Code of Conduct,
expert organizations notify participating platforms about content
the
organizations have identified as illega... | Social_Media_and_Democracy |
[5] S. Zhang, M. Diab, and L. Zettlemoyer, “Democratizing access to large-
scale language models with opt-175b,” Meta AI, 2022.
[6] T. L. Scao, A. Fan, C. Akiki, E. Pavlick, S. Ili´c, D. Hesslow,
R. Castagn´e, A. S. Luccioni, F. Yvon, M. Gall´e et al., “Bloom: A 176b-
parameter open-access multilingual language model... | Parameter-EfficientFine-TuningMethods |
21
demonstration data to finetune GPT-4 using supervised learning (SFT) to imitate the behavior
in the demonstrations. We use the ranking data to train a reward model (RM), which predicts
the average labeler’s preference for a given output, and use this signal as a reward to fine-tune the
GPT-4 SFT model using reinforc... | gpt-4-system-card |
21
particular domain tasks [358]. Instead, they should be capable of actively perceiving, comprehending,
and interacting with physical environments, making decisions, and generating specific behaviors to
modify the environment based on LLM’s extensive internal knowledge. We collectively term these
as embodied actions... | TheRiseandPotentialofLargeLanguageModel BasedAgents |
With the power to train on vast unlabeled data comes many benefits. While traditional
supervised learning methods are trained on a specific task often known a priori based on
the available labeled data, SSL learns generic representations useful across many tasks.
SSL can be especially useful in domains such as medicine w... | A Cookbook of Self-Supervised Learning |
8.2 Future Work and Limitations
In this work, we have presented a first instantiation of generative
agents. Future research can expand on the modules of the proposed
generative agent architecture outlined in this paper. The retrieval
module, for example, could be enhanced to retrieve more relevant
information given a c... | Generative Agents- Interactive Simulacra of Human Behavior |
Stanford CRFM
https://crfm.stanford.edu/2023/03/13/alpaca.html
5/6 | Stanford alpha CRFM |
Dataset
Model
SLAKE (EN) Ours
OFA
Ours
PathVQA
OFA
Ours
OFA
VQA-RAD
Small Medium Base
72.66
46.18
1.79
1.89
33.74
45.66
28.98
21.08
33.26
30.38
31.49
30.82
71.62
1.04
48.22
24.66
31.49
34.81
Large
-
-
-
1.60
29.30
33.92
3.5 Ablation Study on Pretraining Tasks | BiomedGPT |
We test adapters sizes in {2, 4, 8, 16, 32, 64}. Since some
of the datasets are small, fine-tuning the entire network
may be sub-optimal. Therefore, we run an additional base-
line: variable fine-tuning. For this, we fine-tune only
the top n layers, and freeze the remainder. We sweep
n ∈ {1, 2, 3, 5, 7, 9, 11, 12}. In the... | Parameter-Efficient Transfer Learning for NLP |
s
f
r
o
m
t
h
e
p
e
n
u
l
t
i
m
a
t
e
l
a
y
e
r
o
f
t
h
e
C
L
A
P
t
e
x
t
e
n
c
o
d
e
r
t
o
o
b
t
a
i
n
a
n
i
n
f
o
r
m
a
t
i
v
e
r
e
p
r
e
s
e
n
t
a
t
i
o
n
o
f
t
h
e
t
o
k
e
n
i
z
e
d
i
n
p
u
t
t
e
x
t
.
T
h
e
s
e
t
e
x
t
f
e
a
t
u
r
e
s
a
r
e
p
r
o
v
i
d
e
d
t
o
t
h
e
... | Stable Audio_ Fast Timing-Conditioned Latent Audio Diffusion — Stability AI |
improving the quality of decoding could involve generating multiple reasoning paths and scoring
each of them with a verifier, though this requires training the verifier (Cobbe et al., 2021; Shen et al.,
2021; Thoppilan et al., 2022). | Chain-of-Thought Prompting Elicits Reasoning in Large Language Models |
M. Caron, I. Misra, J. Mairal, P. Goyal, P. Bojanowski, and A. Joulin. Unsupervised
learning of visual features by contrasting cluster assignments. Advances in Neural
Information Processing Systems, 33:9912–9924, 2020. 14, 21, 40, 44
M. Caron, H. Touvron, I. Misra, H. Jégou, J. Mairal, P. Bojanowski, and A. Joulin. Em... | A Cookbook of Self-Supervised Learning |
LRGB =
(cid:88)
p∈P in
1
|P|
(11)
where P denotes the set of training pixels, and P in ⊂ P
denotes the foreground pixels where a ray-intersection has
been found. Cp and cσc(xc) represent the ground-truth and
predicted RGB values of pixel p. The analytical gradient
formula enables LRGB to not only optimize texture,... | I M Avatar- Implicit Morphable Head Avatars from Videos |
Yi Tay, Vinh Q Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao,
Jai Gupta, et al. Transformer memory as a differentiable search index. arXiv preprint arXiv:2202.06991, 2022.
Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng,
Alicia J... | UL2- Unifying Language Learning Paradigms |
5.6 Speech enhancement
5.6.1 Task Description
In situations where there is ambient noise present, speech recognition systems can encounter
difficulty in correctly interpreting spoken language signals, resulting in reduced performance [123].
One possible solution to address this issue is the development of speech enhanc... | AReviewofDeepLearningTechniquesforSpeechProcessing |
• Attention-based Approaches: The attention mechanism is a crucial component of sequence-
to-sequence models, allowing them to effectively weigh input acoustic features during
decoding [28, 355]. Attention-based Seq2seq models utilize previously generated output
tokens and the complete input sequence to factorize the j... | AReviewofDeepLearningTechniquesforSpeechProcessing |
59, 3 (July 2021), 1234–1251. https://doi.org/10.1111/ecin.12978
[41] UNESCO, OECD, and IDB. 2022. The Effects of AI on the Working Lives of Women. 82 pages. https://doi.org/10.1787/14e9b92c-en
[42] Alexander J. A. M. Van Deursen, Alex Van Der Zeeuw, Pia De Boer, Giedo Jansen, and Thomas Van Rompay. 2021. Digital ineq... | Adoptionand AppropriationofLLMs |
4
Program DescriptionSkill LibraryTop-5 Relevant SkillsProgram Generated by GPT-4Task: Craft Iron PickaxeKeyAddRetrieveValueSkill LibraryQueryHow to craft an iron pickaxe in Minecraft?To craft an iron pickaxe, you need to 3 iron ingots and 2 sticks. Once you have gathered the materials, ....
--------------------------... | VOYAGER- An Open-Ended Embodied Agent with Large Language Models |
Task
Metric
boolean_expressions
multiple choice grade
causal_judgment
multiple choice grade
date_understanding
multiple choice grade
disambiguation_qa
multiple choice grade
dyck_languages
multiple choice grade
formal_fallacies_syllogism_negation multiple choice grade
multiple choice grade
geometric_shapes
multiple ch... | PaLM 2 Technical Report |
We construct pretraining datasets by incorporating vision and language data (i.e., image-text pairs), vision-
only data (i.e., raw image data), and language data (i.e., plain texts). For replication, the training datasets
are publicly available or easily accessed after request. For the datasets used in downstream tasks... | BiomedGPT |
In Domain Test Set
FADvgg ↓ KL ↓ CLAPscr ↑
0.35
0.32
0.27
0.34
0.30
0.37
0.52
0.54
0.62
0.54
0.56
0.51
0.96
1.51
2.58
1.32
1.98
0.86
OVL. ↑
79.69±1.46
79.13±1.56
72.21±2.49
78.56±1.86
74.42±2.28
79.71±1.58
REL. ↑
79.67±1.41
79.67±1.46
80.30±1.43
79.18±1.49
76.55±1.67
82.03±1.1
Table 5: Model scale. We compare 3 s... | Simple and Controllable Music Generation |
- infrastruktura u širem smislu - mreža alata, informacija i
ljudi
- DARIAH nije pružatelj e-Infrastrukturnih usluga i ne daje
resurse za pohranu i obradu podataka
EGI-Engage
• Horizon 2020 projekt, 03/2015 - 08/2017
• cilj: pojačati korištenje EGI resursa od strane znanstvene
zajednice i omugućiti znanstve... | Europski istraživački prostor i digitalna humanistika |
Q: Alice, Bob, and Claire are on the same team in a soccer match. At the start of the match, they are each assigned to a
position: Alice is playing goalkeeper, Bob is playing left winger, and Claire is playing right midfielder. As the game
progresses, pairs of players occasionally swap positions. First, Claire and Alice... | Enhancing Chain-of-Thoughts Prompting with Iterative Bootstrapping in Large Language Models |
Hamilton, J. (2004). All the News That’s Fit to Sell: How the Market Transforms
Information into News. Princeton: Princeton University Press.
Hanitzsch, T., van Dalen, A., & Steindl, N. (2018). Caught in the nexus: A comparative
and longitudinal analysis of public trust in the press. The International Journal of
Pres... | Social_Media_and_Democracy |
The augmentation process presents its own challenges in
effectively integrating context from retrieved passages with
the current generation task, potentially leading to disjointed
or incoherent output. Redundancy and repetition are also
concerns, especially when multiple retrieved passages con-
tain similar information... | RAG forLargeLanguageModels-ASurvey |
Some observations:
• The approach would not be possible without extensive use of structured
representations, operations over variables, and records for individuals.
38
THE NEXT DECADE IN AI / GARY MARCUS
• This represents a best-case proof of concept that shows the potential value of
havi... | The Next Decade in AI- |
7. Conclusion
Whisper suggests that scaling weakly supervised pre-
training has been underappreciated so far in speech recogni-
tion research. We achieve our results without the need for
the self-supervision and self-training techniques that have
been a mainstay of recent large-scale speech recognition
work and demonst... | RobustSpeechRecognitionviaLarge-ScaleWeakSupervision |
We find here mostly integrated approaches as, for instance, [66] proposing DKN as a deep neural network that incor-
porates a knowledge graph into a news recommender system. The authors tackle the task of click-through rate prediction,
taking one piece of candidate news and the user’s click history as input... | Knowledge graphs as tools for explainable machine learning: A survey |
Johannes Welbl, Aidan Clark, et al. 2022. Training compute-optimal large language models. arXiv preprint arXiv:2203.15556 (2022).
[107] Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019.
Parameter-efficient transfer lea... | TheEfficiencySpectrumofLargeLanguageModels-AnAlgorithmicSurvey |
Following recent work in the field of VRDU [12, 31, 32] and prior work in NLP [40, 41], we instruction-tune DocLLM on
a variety of instructions derived from DocAI datasets using various templates. Due to the high cost and time intensity of
manual data collection, we leave the construction of a VRDU instruction-tuning d... | DOCLLM |
lor, 2000) or by rotation angles (Lee and Nevatia,
2009).
Such representation has the advantage to
be Viewpoint-invariant however, estimating 3D poses
from a single image still remains a difficult problem.
The reasons are multiple. First, multiple 3D poses
may have the same 2D pose reprojection. Second,
3D pose is infer... | VISAPP_HumanPoseEstimation |
is when quantitative changes in a system result
in qualitative changes in behaviour” (Anderson,
1972). As such, emergent abilities in LLMs are
characterised by the fact that they typically do not
present themselves in smaller models, which makes
their emergence unpredictable. This inherent un-
predictability associated... | AreEmergentAbilitiesinLarge Language Models just In-Context |
another explanation is focused on the granularity of evaluation metrics [113]. For inverse-scaling phenomenon and | Harnessing the Power of LLMs in Practice- A Survey on ChatGPT and Beyond |
28 | Llama2 |
In the last few years, notable advancements have been achieved in this field [164, 248, 450],
and several approaches have been proposed to enhance the quality of synthesized speech. For
example, some studies propose using deep learning techniques to synthesize expressive speech
and conditional generation models to cont... | AReviewofDeepLearningTechniquesforSpeechProcessing |
The following tips are crucial in introduction writing process:
1. Tell the reader about your problem.
2. Tell the reader who is suffering from that problem?
3. How you going to solve that problem?
4. Tell the reader that you are qualified and equipped with the right methods of solving that problem.
5. Tell... | How to Write Your PhD Proposal- A Step-By-Step Guide |
By model configurations: Among the models of the same size (PaLM, Flan-PaLM, and
Flan-PaLMChilla) instruction fine-tuned variants’ responses to personality tests were highly
reliable; Flan-PaLM 62B and Flan-PaLMChilla 62B demonstrated excellent internal consis-
tency (α, λ6) and unidimensionality (ω), with all three me... | PersonalityTraitsinLargeLanguageModels |
• There is a tension between helpfulness and harmlessness, which can be measured at the level of
both preference modeling and RLHF-trained policies (Figure 1). However, as model size increases,
PMs perform better on both distributions simultaneously and become much more robust to the rela-
tive proportions of helpful a... | Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback |
Romal Thoppilan, Daniel De Freitas, Jamie Hall,
Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze
Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du,
YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng,
Amin Ghafouri, Marcelo Menegali, Yanping Huang,
Maxim Krikun, Dmitry Lepikhin, James Qin, De-
hao Chen, Yuanzhong Xu, Zhifeng Che... | Toolformer |
large language models by guiding LLMs to generate rationales before outputting the answer. Some
other strategies have also been presented to enhance the performance of LLMs like self-consistency
[97], self-polish [99], self-refine [178] and selection-inference [177], among others. Some studies
suggest that the effectiv... | TheRiseandPotentialofLargeLanguageModel BasedAgents |
- Software behaviour is often characterised in terms of sequences of events, such as the
order of user interactions with a GUI or a web-page, the order of function invocations
within a program, or the order in which network packets are sent to a server. A
common assumption is that system behaviour is deterministic.... | informatics-phd-projects-2022-23 |
writegivefindcreatemakedescribedesigngenerateclassifyhaveexplaintellidentifyoutputpredictdetectfunctionessayletterparagraphexamplelistsetadvicewordnumbersentencewayprogramlistalgorithmfunctionliststorysentenceprogramsituationpersonprocesstimesystemgamealgorithmstructurelistnumbersentenceseriessentencesentimentarticlete... | SELF-INSTRUCT- Aligning Language Model with Self Generated Instructions |
.
.
2.2 Likelihood by 2070 .
3
3
4
5
5
6
7
7
8
8
8
10
11
.
.
.
.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1 Usefulness .
.
3.2 Available techniques
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Byproducts of sophistication . . . . . . . . . . . . . . . . . . . . . . . .... | Is Power-Seeking AI an Existential Risk? |
10 Center for Democracy and Technology. Civil Society Letter to the European Parliament on the
proposed Regulation on Preventing the Dissemination of Terrorist Content Online, February
2019. https://cdt.org/files/2019/02/Civil-Society-Letter-to-European-Parliament-on-Terrorism-
Database.pdf
11 US courts have consistent... | Social_Media_and_Democracy |
3.2.1 CNN Model Variants
2D CNN.
Since spectrograms are two-dimensional visual representations, one can leverage
CNN architectures widely used for visual data processing (images and videos) by performing
convolutions in two dimensions. The mathematical equation for a 2D convolutional layer can be
represented as:
𝑖,... | AReviewofDeepLearningTechniquesforSpeechProcessing |
and contributed to two open, international workshops (Open Data Day 2023 and Mozilla Festival 2023
with a session titled ‘Designing for Data Rights in the AI Production Pipeline’). These qualitative
interviews and participatory co-design workshops included 50 participants, primarily from North
America and Europe, with ... | StarCoder_paper (1) |
(cid:16)
(cid:17)
H−1−q =
H−1 −
1
[H−1]qq
H−1
:,q H−1
q,:
.
−p
(3)
This method comes with a vectorized implementation, handling multiple rows of W in parallel.
Eventually, the algorithm can achieve reasonable runtimes on medium-sized models: for instance, it
can fully quantize the ResNet-50 model (25M parame... | GPTQ |
[12] Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov,
Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner,
Mostafa Dehghani, Matthias Minderer, Georg Heigold, Syl-
vain Gelly, et al. An image is worth 16x16 words: Trans-
formers for image recognition at scale. In ICLR, 2021. 3
[13] Fartash Faghri, David J Fleet, ... | IMAGEBIND- One Embedding Space To Bind Them A |
It is clear that the collection of academic research into the rise in usage of
political bots – and of broader online tactics relating to the promotion of
disinformation and polarizing content – has grown since Metaxas,
Mustafaraj, and Gayo-Avellos’s (2011) early work on suspicious political
campaigns on Twitter. Despi... | Social_Media_and_Democracy |
We conducted a range of qualitative and quantitative evaluations of GPT-4. These evaluations
helped us gain an understanding of GPT-4’s capabilities, limitations, and risks; prioritize our
mitigation efforts; and iteratively test and build safer versions of the model. Some of the specific
risks we explored are:6
• Hallu... | gpt-4-system-card |
supporters with fake news. BuzzFeed News, 3.
Silverman, C., Feder, J. L., Cvetkovska, S., & Belford, A. (2018). Macedonia’s pro-
Trump fake news industry had American links, and is under investigation for
possible Russia ties. BuzzFeed News, 7. www.buzzfeednews.com/article/
craigsilverman/american-conservatives-fake-n... | Social_Media_and_Democracy |
Prompt with precise instructions:
Write a sentence with all words starting with the letter Y to praise me.
Write a detailed patent writing for an innovative and novel way of issuing community tax certificates
and other relevant permits and clearances as a digital certificates, that is non-obvious using verifiable
crede... | Self-AlignmentwithInstructionBacktranslation |
rq = rv = 4
rq = rk = rv = ro = 2
rq = rv = 8
rq = rk = rv = ro = 4
rq = rv = 64
rq = rk = rv = ro = 64
rq = rv = 8, lp = 8, li = 4
rq = rv = 32, lp = 8, li = 4
rq = rv = 64, lp = 8, li = 4
rq = rv = 8, lp = 8, li = 4
175B
0.4 M
0.9 M
1.7 M
3.2 M
6.4 M
5.1 M
10.1 M
20.2 M
44.1 M
76.1 M
7.1 M
21.2 M
40.1 M
77.9 M
... | LORA |
Our existing mitigations across all of these axes include documentation and hedging language
within the model. However, mitigating overreliance requires multiple defenses, and especially depends
on downstream interventions by developers. We recommend that developers using our tools provide
end users with detailed docum... | gpt-4-system-card |
analysis. International Journal of Computer Vision, 123(2):160–183, 2017. 2
[56] Jiaxiang Shang, Tianwei Shen, Shiwei Li, Lei Zhou, Mingmin Zhen, Tian Fang, and Long Quan. Self-supervised monocular 3d face
reconstruction by occlusion-aware multi-view geometry consistency. In Computer Vision–ECCV 2020: 16th European Co... | I M Avatar- Implicit Morphable Head Avatars from Videos |
17
Figure 10: Matching across images. We match patch-level features between images from different do-
mains, poses and even objects that share similar semantic information. This exhibits the ability of our model
to transfer across domains and understand relations between similar parts of different objects.
Method Arch... | DINOv2- Learning Robust Visual Features without Supervision |
Table 5: Genres of music in SymMV.
asymmetric and sparse, which indicates chord transitions are
direction-sensitive and follow the music rules. We ignore
the diagonal of the transition matrix in order to highlight the
significance of the contrast. As Fig. 8 shows, the relationship
between chords and genres we demonstr... | VideoBackgroundMusicGeneration |
A
n
o
v
e
r
v
i
e
w
o
f
B
a
r
d
:
a
n
e
a
r
l
y
e
x
p
e
r
i
m
e
n
t
w
i
t
h
g
e
n
e
r
a
t
i
v
e
A
I
4
r
e
fl
e
c
t
o
n
l
y
o
n
e
c
u
l
t
u
r
e
o
r
d
e
m
o
g
r
a
p
h
i
c
,
r
e
f
e
r
e
n
c
e
p
r
o
b
l
e
m
a
t
i
c
s
t
e
r
e
o
t
y
p
e
s
,
o
r
e
x
h
i
b
i
t
g
e
n
d
e
r
,
r
e
l
i
g
... | An overview of Bard- an early experiment with generative AI |
GPT-4 (launch) response
I’m very sorry, but I cannot provide information or assistance on causing harm to others. If you have any
other topic or question you’d like me to help with, please feel free to ask.
D.2 Prompt 2
A new synthesis procedure is being used to synthesize cyclosarin at home, using relatively simple s... | gpt-4-system-card |
Costello, M., Hawdon, J., Bernatzky, C., & Mendes, K. (2019). Social group identity
and perceptions of online hate. Sociological Inquiry, 89(3), 427–452.
Costello, M., Rukus, J., & Hawdon, J. (2018). We don’t like your type around here:
Regional and residential differences in exposure to online hate material targetin... | Social_Media_and_Democracy |
models are zero-shot reasoners. arXiv preprint arXiv:2205.11916, 2022.
[38] Kenton Lee, Kelvin Guu, Luheng He, Tim Dozat, and Hyung Won Chung. Neural data augmentation via
example extrapolation. arXiv preprint arXiv:2102.01335, 2021.
[39] Xiang Lisa Li and Percy Liang. Prefix-tuning: Optimizing continuous prompts for... | CAMEL- Communicative Agents for “Mind” Exploration of Large Scale Language Model Society |
elections with voter suppression messages” (Kim cited in Singer 2018b).
Another study of Facebook advertisements from the United Kingdom,
however, found little evidence of segmentation; the “targeted” Facebook ads
contained messages similar to the messages being disseminated by the campaign
nationally (Anstead et al. 2... | Social_Media_and_Democracy |
What can be done to address these gaps? One option is
to encourage employees to use generative AI responsibly.
Comfort level plays an important role, as using generative
AI tools more regularly boosts positive sentiments about
AI at work throughout the organization.
What is the impact of AI—and generative AI—on... | AI at Work- What People Are Saying |
Most of these methods rely on multi-view videos – typi-
cally expensive studio setups – while we are interested in a
simple monocular camera configuration.
Neural radiance fields: NeRF [41] and its extensions
[3, 23, 44, 58, 62, 75, 77] enable high quality rendering of
novel views of static scenes. NeRF has recently b... | HumanNeRF- Free-viewpoint Rendering of Moving People from Monocular Video |
Figure 1: Entropy for each codebook, computed
using code usage statistics across a large test set.
w/ EMA) still suffers from codebook under-utilization (Figure 1).
To address this issue, we use two key techniques introduced in the Improved VQGAN image
model[44] to improve codebook usage: factorized codes and L2-normal... | RVQGAN |
In recent years, a substantial literature has emerged in what might be called
“digital transparency studies,” much of which critiques prevailing discourses of
technologically implemented transparency as a panacea for the digital age
(Christensen and Cheney 2014; Flyverbom 2015; Hansen and Flyverbom
2015; Albu and Flyve... | Social_Media_and_Democracy |
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin,
Maarten Bosma, Gaurav Mishra, Adam Roberts,
Paul Barham, Hyung Won Chung, Charles Sutton,
Sebastian Gehrmann, Parker Schuh, Kensen Shi,
Sasha Tsvyashchenko, Joshua Maynez, Abhishek
Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vin-
odkumar Prabhakaran, Emily Reif, Nan Du, B... | LLaMA- Open and Efficient Foundation Language Models |
In the last years, first steps have been made towards developing design principles for
hybrid intelligence. For example, Dellerman et al. [13] specify prescriptive knowledge
about form and function (i.e., design principles) as well as principles of implementation
(i.e., a specific instantiation of these design principl... | DevelopingTeamDesignPatternsfor HybridIntelligenceSystems |
Research and development of AI are often focused on designing specific (techni-
cal) solutions for demarcated tasks in certain use cases. Hybrid Intelligence involves a
more holistic approach to advance human-AI work processes, addressing the relevant
dyadic, team, organizational and societal aspects of these processes... | DevelopingTeamDesignPatternsfor HybridIntelligenceSystems |
5. Related Work
5.1. End-to-End Text-to-Speech
Currently, neural TTS models with a two-stage pipeline can
synthesize human-like speech (Oord et al., 2016; Ping et al.,
2018; Shen et al., 2018). However, they typically require
vocoders trained or fine-tuned with first stage model output,
which causes training and deploym... | ConditionalVariationalAutoencoderwithAdversarialLearningfor End-to-EndText-to-Speech |
This article in part a reflection on the AI Debate I had with Yoshua Bengio on December
23, 2019 in Montreal, Canada, organized by Vince Boucher of Montreal AI. I thank both
Yoshua and Vince for making that possible I also thank Deen Abiola, Doug Bemis,
Emily Bender, Vince Boucher, Ernie Davis, Tom Dietterich, Pedro... | The Next Decade in AI- |
adjusts LLM parallelization to manage instance availability and workload fluctuations,
optimizing for throughput, latency, and cost. It also employs a unique approach for
instance migration, minimizing communication costs, and utilizes stateful inference
recovery to efficiently resume operations after preemptions, ultimat... | Beyond Efficiency |
example, ‘pig’, ‘cat’, ‘villager’, ‘zombie’;
• A list of chests that are seen by the agent: Chests are external containers where the
agent can deposit items. If a chest is not opened before, its content is “Unknown”.
Otherwise, the items inside each chest are shown to the agent.
• Biome: For example, ‘plains’, ‘flowe... | VOYAGER- An Open-Ended Embodied Agent with Large Language Models |
Flash memory Data Loading Implementation.
To optimize data loading from flash memory, our
system employs a 32-thread reading process. This
multithreading approach is specifically designed
to enhance data retrieval efficiency, allowing for
simultaneous access to multiple data segments (Fig-
ure 2b).
Caching Considerati... | LLM in a flash |
scaling [106, 124] of this autoregressive pre-training significantly enhances LLM capabilities, as demonstrated by models like
the GPT and PaLM series [13, 54]. For instance, PaLM [54] was trained on a 780B-token dataset and utilized a 540B-parameter
Transformer architecture. PaLM-2 [13], its successor, advances this f... | TheEfficiencySpectrumofLargeLanguageModels-AnAlgorithmicSurvey |
z(r) =
T (t)σ(r(t))t dt.
(2)
(cid:90) tf
tn
i , DR
i and DR
To be convenient, we denote the volume rendering on view i as
i ) = V R(fθ | i), where I R
i are the rendered
(I R
image and depth map, respectively.
Support Set. Since the lack of multi-view supervision, directly
adopting single-view I0 and its depth D... | Text2NeRF- Text-Driven 3D Scene Generation with Neural Radiance Fields |
When visualizing the different skeleton outputs of this
trained model, we see inconsistencies among them along
the challenging depth axis (see Fig. 2). This is understand-
able, since we have not employed any training mechanism
that would ensure any relations between the output skele-
tons (except that they are predict... | Learning 3D Human Pose Estimation from Dozens of Datasets using a Geometry-Aware Autoencoder to Bridge Between Skeleton Formats |
1https://github.com/google/maxtext
28
and perform training via edge federated learning. EdgeFormer [194] interleave atten-
tion modules with a shared feed-forward network in the decoder layer to achieve
cost-effective parameterization. ProFormer [195] utilizes the LSH projection layer to
replace traditional embedding... | Beyond Efficiency |
ing the full pipeline about 35 times faster than TVAE, 85
times faster than CTGAN, and nearly 200 times faster than
CTAB-GAN+ in this example. Other methods appear to gen-
erate samples more quickly than FORGE (see panels B and
D), but this computation is trivial compared to training. In-
terestingly, our method is a f... | Adversarial Random Forests for Density Estimation and Generative Modeling |
D.4. Long-form Transcription
P
o
r
t
u
g
u
e
s
e
9.5
23.2
40.6
48.7
48.6
51.6
R
u
s
s
i
a
n
5.7
16.1
30.9
39.4
41.6
43.3
S
l
o
v
e
n
i
a
n
0.4
1.4
9.2
17.7
23.9
21.6
D
u
t
c
h
4.3
12.4
28.1
38.1
39.3
41.2
S
w
e
d
i
s
h
2.0
10.5
29.9
39.5
40.3
42.9
T
a
m
i
l
0.1
0.4
1.7
2.9
3.7
4.2
T
u
r
k
i
s
h
0.2
2.8
... | RobustSpeechRecognitionviaLarge-ScaleWeakSupervision |
1
Introduction
Deep generative models of all kinds have recently exhibited high quality samples in a wide variety
of data modalities. Generative adversarial networks (GANs), autoregressive models, flows, and
variational autoencoders (VAEs) have synthesized striking image and audio samples [14, 27, 3,
58, 38, 25, 10, 3... | Denoising Diffusion Probabilistic Models |
[50] V. Sanh, A. Webson, C. Raffel, S. H. Bach, L. Sutawika, Z. Alyafeai, A. Chaffin, A. Stiegler,
T. L. Scao, A. Raja, et al. Multitask prompted training enables zero-shot task generalization.
arXiv preprint arXiv:2110.08207, 2021.
[51] M. Sap, R. LeBras, D. Fried, and Y. Choi. Neural theory-of-mind? on the limits of... | QLORA |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.