- See Also
- Gwern
-
Links
- “Why Concepts Are (probably) Vectors”, Piantadosi et al 2024
- “Using Counterfactual Tasks to Evaluate the Generality of Analogical Reasoning in Large Language Models”, Lewis & Mitchell 2024
- “A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models”, Eisape et al 2023
- “Getting from Generative AI to Trustworthy AI: What LLMs Might Learn from Cyc”, Lenat & Marcus 2023
- “Evaluating Superhuman Models With Consistency Checks”, Fluri et al 2023
- “LLM+P: Empowering Large Language Models With Optimal Planning Proficiency”, Liu et al 2023
- “Humans in Humans Out: On GPT Converging Toward Common Sense in Both Success and Failure”, Koralus & Wang-Maścianica 2023
- “Tighter Bounds on the Expressivity of Transformer Encoders”, Chiang et al 2023
- “Emergent Analogical Reasoning in Large Language Models”, Webb et al 2022
- “Discovering Latent Knowledge in Language Models Without Supervision”, Burns et al 2022
- “Deep Differentiable Logic Gate Networks”, Petersen et al 2022
- “Transformers Implement First-Order Logic With Majority Quantifiers”, Merrill & Sabharwal 2022
- “FOLIO: Natural Language Reasoning With First-Order Logic”, Han et al 2022
- “Language Models Show Human-Like Content Effects on Reasoning”, Dasgupta et al 2022
- “Mathematical Proof Between Generations”, Bayer et al 2022
- “Maieutic Prompting: Logically Consistent Reasoning With Recursive Explanations”, Jung et al 2022
- “On the Paradox of Learning to Reason from Data”, Zhang et al 2022
- “Logical Intuition Is Not Really About Logic”, Ghasemi et al 2022
- “Logical Activation Functions: Logit-Space Equivalents of Probabilistic Boolean Operators”, Lowe et al 2021
- “Catala: A Programming Language for the Law”, Merigoux et al 2021
- “How the Slowest Computer Programs Illuminate Math’s Fundamental Limits: The Goal of the ‘Busy Beaver’ Game Is to Find the Longest-Running Computer Program. Its Pursuit Has Surprising Connections to Some of the Most Profound Questions and Concepts in Mathematics”, Pavlus 2020
- “On the Measure of Intelligence”, Chollet 2019
- “Best Practices: Formal Proofs, the Fine Print and Side Effects”, Murray & Oorschot 2018
- “A Logic for Statutes”, Lawsky 2017
- “How Did Software Get So Reliable Without Proof? [Blog]”, Regehr 2012
- “Why Philosophers Should Care About Computational Complexity”, Aaronson 2011
- “Good and Real: Demystifying Paradoxes from Physics to Ethics § 1.2.3: Paradoxes: When Arguments Collide”, Drescher 2006 (page 39)
- “Philosophical Problems in Logic § Ultrafinitism”, Friedman 2002 (page 4)
- “An Editor Recalls Some Hopeless Papers”, Hodges 1998
- “How Did Software Get so Reliable without Proof?”, Hoare 1996
- “An Epistemological Nightmare”, Smullyan 1982
- “Nonstandard Analysis”, Davis & Hersh 1972b
- “‘Begging the Question’”, Sparkes 1966
- “A Plea for Excuses: The Presidential Address”, Austin 1956
- “John Wilkins’s Analytical Language”, Borges 1942
- “Symposium: Facts and Propositions”, Ramsey & Moore 1927
- “Review of Tractatus Logico-Philosophicus by Ludwig Wittgenstein”, Ramsey 1923
- “In Strategic Time, Open-Source Games Are Loopy”
- “Mathematical Notation: Past and Future”
- Sort By Magic
- Wikipedia
- Miscellaneous
- Bibliography
See Also
Gwern
“Abs-E (or, Speak Only in the Positive) § text2epositive.py Experiment”, Gwern 2024
Abs-E (or, speak only in the positive) § text2epositive.py experiment
“Abs-E (or, Speak Only in the Positive) § text2epositive.py Experiment”, Gwern 2024
Abs-E (or, speak only in the positive) § text2epositive.py experiment
“text2epositive.py”, Gwern 2024
“One Man’s Modus Ponens”, Gwern 2012
Links
“Why Concepts Are (probably) Vectors”, Piantadosi et al 2024
“Using Counterfactual Tasks to Evaluate the Generality of Analogical Reasoning in Large Language Models”, Lewis & Mitchell 2024
“A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models”, Eisape et al 2023
A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models
“Getting from Generative AI to Trustworthy AI: What LLMs Might Learn from Cyc”, Lenat & Marcus 2023
Getting from Generative AI to Trustworthy AI: What LLMs might learn from Cyc
“Evaluating Superhuman Models With Consistency Checks”, Fluri et al 2023
“LLM+P: Empowering Large Language Models With Optimal Planning Proficiency”, Liu et al 2023
LLM+P: Empowering Large Language Models with Optimal Planning Proficiency
“Humans in Humans Out: On GPT Converging Toward Common Sense in Both Success and Failure”, Koralus & Wang-Maścianica 2023
Humans in Humans Out: On GPT Converging Toward Common Sense in both Success and Failure
“Tighter Bounds on the Expressivity of Transformer Encoders”, Chiang et al 2023
“Emergent Analogical Reasoning in Large Language Models”, Webb et al 2022
“Discovering Latent Knowledge in Language Models Without Supervision”, Burns et al 2022
Discovering Latent Knowledge in Language Models Without Supervision
“Deep Differentiable Logic Gate Networks”, Petersen et al 2022
“Transformers Implement First-Order Logic With Majority Quantifiers”, Merrill & Sabharwal 2022
Transformers Implement First-Order Logic with Majority Quantifiers
“FOLIO: Natural Language Reasoning With First-Order Logic”, Han et al 2022
“Language Models Show Human-Like Content Effects on Reasoning”, Dasgupta et al 2022
Language models show human-like content effects on reasoning
“Mathematical Proof Between Generations”, Bayer et al 2022
“Maieutic Prompting: Logically Consistent Reasoning With Recursive Explanations”, Jung et al 2022
Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations
“On the Paradox of Learning to Reason from Data”, Zhang et al 2022
“Logical Intuition Is Not Really About Logic”, Ghasemi et al 2022
“Logical Activation Functions: Logit-Space Equivalents of Probabilistic Boolean Operators”, Lowe et al 2021
Logical Activation Functions: Logit-space equivalents of Probabilistic Boolean Operators
“Catala: A Programming Language for the Law”, Merigoux et al 2021
“How the Slowest Computer Programs Illuminate Math’s Fundamental Limits: The Goal of the ‘Busy Beaver’ Game Is to Find the Longest-Running Computer Program. Its Pursuit Has Surprising Connections to Some of the Most Profound Questions and Concepts in Mathematics”, Pavlus 2020
“On the Measure of Intelligence”, Chollet 2019
“Best Practices: Formal Proofs, the Fine Print and Side Effects”, Murray & Oorschot 2018
Best Practices: Formal Proofs, the Fine Print and Side Effects
“A Logic for Statutes”, Lawsky 2017
“How Did Software Get So Reliable Without Proof? [Blog]”, Regehr 2012
How Did Software Get So Reliable Without Proof? [blog]:
View External Link:
“Why Philosophers Should Care About Computational Complexity”, Aaronson 2011
“Good and Real: Demystifying Paradoxes from Physics to Ethics § 1.2.3: Paradoxes: When Arguments Collide”, Drescher 2006 (page 39)
“Philosophical Problems in Logic § Ultrafinitism”, Friedman 2002 (page 4)
“An Editor Recalls Some Hopeless Papers”, Hodges 1998
“How Did Software Get so Reliable without Proof?”, Hoare 1996
“An Epistemological Nightmare”, Smullyan 1982
“Nonstandard Analysis”, Davis & Hersh 1972b
View PDF:
“‘Begging the Question’”, Sparkes 1966
View PDF:
“A Plea for Excuses: The Presidential Address”, Austin 1956
“John Wilkins’s Analytical Language”, Borges 1942
“Symposium: Facts and Propositions”, Ramsey & Moore 1927
Symposium: Facts and Propositions:
View PDF:
“Review of Tractatus Logico-Philosophicus by Ludwig Wittgenstein”, Ramsey 1923
Review of Tractatus Logico-Philosophicus by Ludwig Wittgenstein
“In Strategic Time, Open-Source Games Are Loopy”
“Mathematical Notation: Past and Future”
Sort By Magic
Annotations sorted by machine learning into inferred 'tags'. This provides an alternative way to browse: instead of by date order, one can browse in topic order. The 'sorted' list has been automatically clustered into multiple sections & auto-labeled for easier browsing.
Beginning with the newest annotation, it uses the embedding of each annotation to attempt to create a list of nearest-neighbor annotations, creating a progression of topics. For more details, see the link.
planning-proficiency
reasoning-logic learning-analogies reasoning-models logical-reasoning language-logic
legal-philosophy
Wikipedia
Miscellaneous
Bibliography
-
https://arxiv.org/abs/2308.04445: “Getting from Generative AI to Trustworthy AI: What LLMs Might Learn from Cyc”, -
https://arxiv.org/abs/2209.00840: “FOLIO: Natural Language Reasoning With First-Order Logic”, -
2022-ghasemi.pdf: “Logical Intuition Is Not Really About Logic”, -
https://www.quantamagazine.org/how-the-slowest-computer-programs-illuminate-maths-fundamental-limits-20201210/: “How the Slowest Computer Programs Illuminate Math’s Fundamental Limits: The Goal of the ‘Busy Beaver’ Game Is to Find the Longest-Running Computer Program. Its Pursuit Has Surprising Connections to Some of the Most Profound Questions and Concepts in Mathematics”,