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1eac87104b72d4ab
Faithfulness vs. plausibility: On the (un) reliability of explanations from large language models
Chirag Agarwal; Sree Harsha Tanneru; Himabindu Lakkaraju
2024
d917cd028733ed65
Using contents and containers to investigate problem solving strategies among toddlers
Zaid Alkouri
2016. 2025. 2025-02-21. 1, 34
119ba272169c311c
Generalized energy based models
Michael Arbel; Liang Zhou; Arthur Gretton
2020
2e98e4fd0f964692
Residual energy-based models for text
Anton Bakhtin; Yuntian Deng; Sam Gross; Myle Ott; Marc'aurelio Ranzato; Arthur Szlam
2021
47b4affde903ebf9
The reversal curse: Llms trained on" a is b" fail to learn" b is a
Lukas Berglund; Meg Tong; Max Kaufmann; Mikita Balesni; Asa Cooper Stickland; Tomasz Korbak; Owain Evans
2023
9ae49c0d9a21077d
A conceptual introduction to hamiltonian monte carlo
Michael Betancourt
2017
dc52ea9368ee8d85
Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models
Sumanta Bhattacharyya; Amirmohammad Rooshenas; Subhajit Naskar; Simeng Sun; Mohit Iyyer; Andrew Mccallum
2020
10.18653/v1/2021.acl-long.349
75fef152d6e5750f
Jones, Most Rev. Christopher, (born 3 March 1936), Bishop of Elphin, (RC), 1994–2014, now Bishop Emeritus
M Christopher; Bishop
1994
10.1093/ww/9780199540884.013.14922
7e538a59d9429972
GPT-NeoX-20B: An Open-Source Autoregressive Language Model
Sidney Black; Stella Biderman; Eric Hallahan; Quentin Anthony; Leo Gao; Laurence Golding; Horace He; Connor Leahy; Kyle Mcdonell; Jason Phang; Michael Pieler; Usvsn Sai Prashanth; Shivanshu Purohit; Laria Reynolds; Jonathan Tow; Ben Wang; Samuel Weinbach
2022
10.18653/v1/2022.bigscience-1.9
e76f99d5c51d2c25
AudioLM: A Language Modeling Approach to Audio Generation
Zalán Borsos; Raphaël Marinier; Damien Vincent; Eugene Kharitonov; Olivier Pietquin; Matt Sharifi; Dominik Roblek; Olivier Teboul; David Grangier; Marco Tagliasacchi; Neil Zeghidour
2023
10.1109/taslp.2023.3288409
c51c3ff23608f05a
Transformer flops
Adam Casson
2023
a570e740620f4202
Neural ordinary differential equations
Yulia Ricky Tq Chen; Jesse Rubanova; David K Bettencourt; Duvenaud
2018
a741c40e6bbb31b2
Learning to stop while learning to predict
Xinshi Chen; Hanjun Dai; Yu Li; Xin Gao; Le Song
2020
76a24a292d4e682e
Scaling laws for predicting downstream performance in llms
Yangyi Chen; Binxuan Huang; Yifan Gao; Zhengyang Wang; Jingfeng Yang; Heng Ji
2024
c27f48416ddbd74a
Diffusion Policy: Visuomotor Policy Learning via Action Diffusion
Cheng Chi; Siyuan Feng; Yilun Du; Zhenjia Xu; Eric Cousineau; Benjamin Burchfiel; Shuran Song
2023
10.15607/rss.2023.xix.026
0833d4b357c96849
Training verifiers to solve math word problems
Karl Cobbe; Vineet Kosaraju; Mohammad Bavarian; Mark Chen; Heewoo Jun; Lukasz Kaiser; Matthias Plappert; Jerry Tworek; Jacob Hilton; Reiichiro Nakano
2021
dd2d242a41ee9f6a
Redpajama: an open dataset for training large language models
2023
e051ed02ad600d82
The complexity of theorem-proving procedures
A Stephen; Cook
2023
922f39f53dab2b95
How to compute hessian-vector products? In ICLR Blogposts
Mathieu Dagréou; Pierre Ablin; Samuel Vaiter; Thomas Moreau
2024. 2024. 27, 31, 33
8304dd6378ccfafb
Introduction to latent variable energy-based models: a path toward autonomous machine intelligence
Anna Dawid; Yann Lecun
2024. 2024
10.1088/1742-5468/ad292b
e974954191a57916
Universal transformers
Mostafa Dehghani; Stephan Gouws; Oriol Vinyals; Jakob Uszkoreit; Łukasz Kaiser
2018
a0d95644c329b8e2
Causal diffusion transformers for generative modeling
Chaorui Deng; Deyao Zhu; Kunchang Li; Shi Guang; Haoqi Fan
2024
0faf6e244f850803
Autoregressive Image Generation without Vector Quantization
Mingyang Deng; Kaiming He; He Li; Tianhong Li; Yonglong Tian
2024
10.52202/079017-1797
7c1089cfe1e14322
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin; Ming-Wei Chang; Kenton Lee; Kristina Toutanova
2019
818ba10ca0a1023b
Evidence for time‐variant decision making
Jochen Ditterich
2006
10.1111/j.1460-9568.2006.05221.x
3be13385afa95e80
Recurrent neuronal circuits in the neocortex
J Rodney; Kevan Ac Douglas; Martin
2007
1b8072188b06103f
Implicit generation and modeling with energy based models
Yilun Du; Igor Mordatch
2019
8256ef3542af02f7
Improved contrastive divergence training of energy based models
Yilun Du; Shuang Li; Joshua Tenenbaum; Igor Mordatch
2020
31f6cbceea83bea8
Learning iterative reasoning through energy minimization
Yilun Du; Shuang Li; Joshua Tenenbaum; Igor Mordatch
2022
fbfa2b5a68dd0bde
Reduce, reuse, recycle: Compositional generation with energy-based diffusion models and mcmc
Yilun Du; Conor Durkan; Robin Strudel; Joshua B Tenenbaum; Sander Dieleman; Rob Fergus; Jascha Sohl-Dickstein; Arnaud Doucet; Will Sussman; Grathwohl
2023
4fe5711e407289ed
Learning iterative reasoning through energy diffusion
Yilun Du; Jiayuan Mao; Joshua B Tenenbaum
2024
0699a709305b036a
Dual-process theories of reasoning: Contemporary issues and developmental applications
Jonathan St; B T Evans
2011
e9854d0cc8594b72
Pytorch lightning
William A Falcon
2019
266c5e9e0b556b04
Dual-process and dual-system theories of reasoning
Keith Frankish
2010
107be4cd1b44d62a
Mapping sentence form onto meaning: The syntax-semantic interface
D Angela; Jürgen Friederici; Weissenborn
2007
f5555c8731afc354
Scaling up test-time compute with latent reasoning: A recurrent depth approach
Jonas Geiping; Sean Mcleish; Neel Jain; John Kirchenbauer; Siddharth Singh; Brian R Bartoldson; Bhavya Kailkhura; Abhinav Bhatele; Tom Goldstein
2025
69dbe9d1670d1f8d
Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot; Yoshua Bengio
2010
aae05b4139e08cbe
Dissociation of Mechanisms Underlying Syllogistic Reasoning
Vinod Goel; Christian Buchel; Chris Frith; Raymond J Dolan
2000
10.1006/nimg.2000.0636
f1663246dc62c528
The knowledge complexity of interactive proof-systems
Shafi Goldwasser; Silvio Micali; Chales Rackoff
2019
10.1145/3335741.3335750
bdaa0fd7d70f6b8b
Generative adversarial nets
Ian J Goodfellow; Jean Pouget-Abadie; Mehdi Mirza; Bing Xu; David Warde-Farley; Sherjil Ozair; Aaron Courville; Yoshua Bengio
2014
53632141927c5bf7
The" something something" video database for learning and evaluating visual common sense
Raghav Goyal; Samira Ebrahimi Kahou; Vincent Michalski; Joanna Materzynska; Susanne Westphal; Heuna Kim; Valentin Haenel; Ingo Fruend; Peter Yianilos; Moritz Mueller-Freitag
2017
e7798aab2bca4e34
The llama 3 herd of models
Aaron Grattafiori; Abhimanyu Dubey; Abhinav Jauhri; Abhinav Pandey; Abhishek Kadian; Ahmad Al-Dahle; Aiesha Letman; Akhil Mathur; Alan Schelten; Alex Vaughan
2024
1d515b73716952ac
Mamba: Linear-time sequence modeling with selective state spaces
Albert Gu; Tri Dao
2023. 7, 20, 29, 30
d7b06ad53db33060
Long-context autoregressive video modeling with next-frame prediction
Yuchao Gu; Weijia Mao; Mike Zheng Shou
2025
db855cc92a579c77
Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Dejian Daya Guo; Haowei Yang; Junxiao Zhang; Ruoyu Song; Runxin Zhang; Qihao Xu; Shirong Zhu; Peiyi Ma; Xiao Wang; Bi
2025
a375e8ea3dcf4c65
ძალადობაგამოვლილი ქალების გამოხატვის თავისუფლების შეზღუდვის გენდერულ დისკრიმინაციად კვალიფიკაცია
Ქეთევან Ბახტაძე
1956. 2025-04-28
10.63410/9789941862557
892ec28136a4c099
Training large language models to reason in a continuous latent space
Shibo Hao; Sainbayar Sukhbaatar; Dijia Su; Xian Li; Zhiting Hu; Jason Weston; Yuandong Tian
2024
6697b5db79afaae3
Out-of-Distribution Detection with a Single Unconditional Diffusion Model
Alvin Heng; Harold Soh; Alexandre Thiery
2024
10.52202/079017-1395
f95ada3ff042df51
Denoising diffusion probabilistic models
Jonathan Ho; Ajay Jain; Pieter Abbeel
2020
9594e1d660521c16
Training compute-optimal large language models
Jordan Hoffmann; Sebastian Borgeaud; Arthur Mensch; Elena Buchatskaya; Trevor Cai; Eliza Rutherford; Diego De Las; Lisa Anne Casas; Johannes Hendricks; Aidan Welbl; Clark
2022
7ce1a1fd8bc84a6c
Energy transformer
Benjamin Hoover; Yuchen Liang; Bao Pham; Rameswar Panda; Hendrik Strobelt; Horng Duen; Mohammed Chau; Dmitry Zaki; Krotov
2024
700c981212db543f
Neural networks and physical systems with emergent collective computational abilities
J John; Hopfield
1982
ca6c595319fc8a58
Predicting emergent abilities with infinite resolution evaluation
Shengding Hu; Xin Liu; Xu Han; Xinrong Zhang; Chaoqun He; Weilin Zhao; Yankai Lin; Ning Ding; Zebin Ou; Guoyang Zeng
2023
b458b4068715f944
T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation
Kaiyi Huang; Kaiyue Sun; Enze Xie; Zhenguo Li; Xihui Liu
2023
28a1aa9fb6a0b534
Diffusion models for video prediction and infilling
Tobias Höppe; Arash Mehrjou; Stefan Bauer; Didrik Nielsen; Andrea Dittadi
2022
9121c98f8bb0db16
Time matters: Scaling laws for any budget
Itay Inbar; Luke Sernau
2024
d09f6d17d4f66a54
Scaling laws for downstream task performance of large language models
Berivan Isik; Natalia Ponomareva; Hussein Hazimeh; Dimitris Paparas; Sergei Vassilvitskii; Sanmi Koyejo
2024
19ce611200bee20d
PATRON: Perspective-Aware Multitask Model for Referring Expression Grounding Using Embodied Multimodal Cues
Md Mofijul Islam; Alexi Gladstone; Tariq Iqbal
2023
10.1609/aaai.v37i1.25177
d117922890a7e2ce
Openai o1 system card
Aaron Jaech; Adam Kalai; Adam Lerer; Adam Richardson; Ahmed El-Kishky; Aiden Low; Alec Helyar; Aleksander Madry; Alex Beutel; Alex Carney
2024
735ba92505a794a6
Planning with diffusion for flexible behavior synthesis
Michael Janner; Yilun Du; Joshua B Tenenbaum; Sergey Levine
2022
9b6ee1284dc49a77
Less is More: Recursive Reasoning with Tiny Networks
Alexia Jolicoeur-Martineau
2025
10.21203/rs.3.rs-8148771/v1
226fa0fb2c026cd7
Thinking, fast and slow
Daniel Kahneman
2011
336a35cdbef2266d
Representativeness revisited: Attribute substitution in intuitive judgment
Shane Daniel Kahneman; Frederick
2002
ddaf29eaf8251d17
Position: Llms can't plan, but can help planning in llm-modulo frameworks
Subbarao Kambhampati; Karthik Valmeekam; Lin Guan; Mudit Verma; Kaya Stechly; Siddhant Bhambri; Lucas Paul Saldyt; Anil B Murthy
2024
075823e757f3a655
Scaling laws for neural language models
Jared Kaplan; Sam Mccandlish; Tom Henighan; Tom B Brown; Benjamin Chess; Rewon Child; Scott Gray; Alec Radford; Jeffrey Wu; Dario Amodei
2020
dfb4f0dd4eb2b831
Auto-encoding variational bayes
Max Diederik P Kingma; Welling
2013
2ef3345ace04127c
When can transformers compositionally generalize in-context?
Seijin Kobayashi; Simon Schug; Yassir Akram; Florian Redhardt; Razvan Johannes Von Oswald; Guillaume Pascanu; João Lajoie; Sacramento
2024
11023d0814c04f19
Transformers in speech processing: Overcoming challenges and paving the future
Siddique Latif; Syed Aun Muhammad Zaidi; Heriberto Cuayáhuitl; Fahad Shamshad; Moazzam Shoukat; Muhammad Usama; Junaid Qadir
2023
10.1016/j.cosrev.2025.100768
fe5d4268c1e63d74
A survey on the applications of zero-knowledge proofs
Ryan Lavin; Xuekai Liu; Hardhik Mohanty; Logan Norman; Giovanni Zaarour; Bhaskar Krishnamachari
2024
5c415052ac8cfe9c
A path towards autonomous machine intelligence version 0
Yann Lecun
2022
24fdd1f9b58d78a2
Energy-Based Models
Yann Lecun; Sumit Chopra; Raia Hadsell; Marc'aurelio Ranzato; Fu Jie Huang
2006
10.7551/mitpress/7443.003.0014
79adba13ad1a0770
Alias-Free Mamba Neural Operator
Wei Li; Xiaoxu Lin; Ni Xu; Xiaoqin Zhang; Jianwei Zheng; Junwei Zhu
2018
10.52202/079017-1678
767aa7c73e8ceb62
mis) fitting: A survey of scaling laws
Margaret Li; Sneha Kudugunta; Luke Zettlemoyer
2025
a0acffb68ce145b4
Autoregressive image generation without vector quantization
Tianhong Li; Yonglong Tian; He Li; Mingyang Deng; Kaiming He
2025
34f8f65eb304090f
Learning Energy-Based Models in High-Dimensional Spaces with Multiscale Denoising-Score Matching
Zengyi Li; Yubei Chen; Friedrich T Sommer
2023
10.3390/e25101367
aec689a39766608c
From system 1 to system 2: A survey of reasoning large language models
Zhong-Zhi Li; Duzhen Zhang; Ming-Liang Zhang; Jiaxin Zhang; Zengyan Liu; Yuxuan Yao; Haotian Xu; Junhao Zheng; Pei-Jie Wang; Xiuyi Chen
2025
0fc9d9ad7d3d9d69
Let's verify step by step
Vineet Hunter Lightman; Yuri Kosaraju; Harrison Burda; Bowen Edwards; Teddy Baker; Jan Lee; John Leike; Ilya Schulman; Karl Sutskever; Cobbe
2023
8ba3ad322af4dd08
Implicit Reasoning in Transformers is Reasoning through Shortcuts
Tianhe Lin; Jian Xie; Siyu Yuan; Deqing Yang
2025
10.18653/v1/2025.findings-acl.493
4f02b2008b9399bb
Microsoft COCO: Common Objects in Context
Tsung-Yi Lin; Michael Maire; Serge Belongie; James Hays; Pietro Perona; Deva Ramanan; Piotr Dollár; C Lawrence Zitnick
September 6-12, 2014. 2014
10.1007/978-3-319-10602-1_48
71d27988cfedc971
Video-t1: Test-time scaling for video generation
Fangfu Liu; Hanyang Wang; Yimo Cai; Kaiyan Zhang; Xiaohang Zhan; Yueqi Duan
2025
a992f9eb67b72f81
Compositional Visual Generation with Composable Diffusion Models
Nan Liu; Shuang Li; Yilun Du; Antonio Torralba; Joshua B Tenenbaum
2022
10.1007/978-3-031-19790-1_26
c7a845bf2cfc695f
Paving the Way to Eureka—Introducing “Dira” as an Experimental Paradigm to Observe the Process of Creative Problem Solving
Frank Loesche; Jeremy Goslin; Guido Bugmann
2018
10.3389/fpsyg.2018.01773
12f90346fe20a323
Scaling Inference Time Compute for Diffusion Models
Nanye Ma; Shangyuan Tong; Haolin Jia; Hexiang Hu; Yu-Chuan Su; Mingda Zhang; Xuan Yang; Yandong Li; Tommi Jaakkola; Xuhui Jia; Saining Xie
2025. 24, 34, 35
10.1109/cvpr52734.2025.00241
097d9e7eef0cb537
Adaptive inference-time compute: Llms can predict if they can do better, even mid-generation
Rohin Manvi; Anikait Singh; Stefano Ermon
2024
1498743f0b1411f5
Gsm-symbolic: Understanding the limitations of mathematical reasoning in large language models
Iman Mirzadeh; Keivan Alizadeh; Hooman Shahrokhi; Oncel Tuzel; Samy Bengio; Mehrdad Farajtabar
2024
5d2a7b52f413a2b8
Do deep generative models know what they don't know?
Eric Nalisnick; Akihiro Matsukawa; Yee Whye Teh; Dilan Gorur; Balaji Lakshminarayanan
2018
7b2c8c3b73d6931f
Dual processing in reasoning: Two systems but one reasoner
Wim De; Neys
2006
bf9fe954d743eb9f
Learning to reason with llms
Openai
2024. 2025-02-21
3f874761e46a3eae
Dinov2: Learning robust visual features without supervision
Maxime Oquab; Timothée Darcet; Théo Moutakanni; Huy Vo; Marc Szafraniec; Vasil Khalidov; Pierre Fernandez; Daniel Haziza; Francisco Massa; Alaaeldin El-Nouby; Mahmoud Assran; Nicolas Ballas; Wojciech Galuba; Russell Howes; Po-Yao Huang; Shang-Wen Li; Ishan Misra; Michael Rabbat; Vasu Sharma; Gabriel Synnaeve; Hu Xu; Hervé Jegou; Julien Mairal; Patrick Labatut; Armand Joulin; Piotr Bojanowski
2023
bf70f23dd3bcb8ab
Recurrent relational networks
Rasmus Palm; Ulrich Paquet; Ole Winther
2018
31bf76013a0da389
Active Inference
Thomas Parr; Giovanni Pezzulo; Karl J Friston
2022
10.7551/mitpress/12441.001.0001
44c9a1e759ec78a4
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke; Sam Gross; Francisco Massa; Adam Lerer; James Bradbury; Gregory Chanan; Trevor Killeen; Zeming Lin; Natalia Gimelshein; Luca Antiga
2019
ad40f763a2e82371
Fast exact multiplication by the hessian
A Barak; Pearlmutter
1994
f09dace0fc88aee8
Scalable Diffusion Models with Transformers
William Peebles; Saining Xie
2023
10.1109/iccv51070.2023.00387
f7178753fd671bef
Transformer uncertainty estimation with hierarchical stochastic attention
Jiahuan Pei; Cheng Wang; György Szarvas
2022
24ffd3fc4d1192f5
The fineweb datasets: Decanting the web for the finest text data at scale
Guilherme Penedo; Hynek Kydlíček; Anton Lozhkov; Margaret Mitchell; Colin A Raffel; Leandro Von Werra; Thomas Wolf
2024
119da46d6798b66b
RWKV: Reinventing RNNs for the Transformer Era
Bo Peng; Eric Alcaide; Quentin Anthony; Alon Albalak; Samuel Arcadinho; Stella Biderman; Huanqi Cao; Xin Cheng; Michael Chung; Leon Derczynski; Xingjian Du; Matteo Grella; Kranthi Gv; Xuzheng He; Haowen Hou; Przemyslaw Kazienko; Jan Kocon; Jiaming Kong; Bartłomiej Koptyra; Hayden Lau; Jiaju Lin; Krishna Sri Ipsit Mantri; Ferdinand Mom; Atsushi Saito; Guangyu Song; Xiangru Tang; Johan Wind; Stanisław Woźniak; Zhenyuan Zhang; Qinghua Zhou; Jian Zhu; Rui-Jie Zhu
2023
10.18653/v1/2023.findings-emnlp.936
59fab88661af3697
Uncertainty and stress: Why it causes diseases and how it is mastered by the brain
Achim Peters; Bruce S Mcewen; Karl J Friston
2017
10.1016/j.pneurobio.2017.05.004
17c2a4cd24811659
Figure 8: Demonstration of continued pre-training of LLaMA2 models in combination of pre-training instructional datasets (Xie et al., 2025).
Alec Radford; Karthik Narasimhan; Tim Salimans; Ilya Sutskever
2018
10.7717/peerj-cs.3216/fig-8
578147b8e3900f56
Language models are unsupervised multitask learners
Alec Radford; Jeffrey Wu; Rewon Child; David Luan; Dario Amodei; Ilya Sutskever
2019
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