5 citations · 11 across the 10 of their papers we have counts for
10 papers
ABC implies that Ramanujan's tau function misses almost all primes
David Kurniadi Angdinata, Evan Chen, Chris Cummins +21
Lehmer conjectured that Ramanujan's tau-function never vanishes. In a related direction, a folklore conjecture asserts that infinitely many primes arise as absolute values of Raman…
Dead ends in square-free digit walks
Evan Chen, Chris Cummins, Ben Eltschig +18
We study "dead ends" in square-free digit walks: square-free integers such that, in base , every one-digit extension is non-square-free. In base , the stochastic…
Fel's Conjecture on Syzygies of Numerical Semigroups
Evan Chen, Chris Cummins, GSM +18
Let be a numerical semigroup and its semigroup ring. The Hilbert numerator of determines normalized alternating syzygy power sums $K_…
CWM: An Open-Weights LLM for Research on Code Generation with World Models
FAIR CodeGen team, Jade Copet, Quentin Carbonneaux +48
We release Code World Model (CWM), a 32-billion-parameter open-weights LLM, to advance research on code generation with world models. To improve code understanding beyond what can…
What I cannot execute, I do not understand: Training and Evaluating LLMs on Program Execution Traces
Jordi Armengol-Estapé, Quentin Carbonneaux, Tianjun Zhang +8
Code generation and understanding are critical capabilities for large language models (LLMs). Thus, most LLMs are pretrained and fine-tuned on code data. However, these datasets ty…
Don't Transform the Code, Code the Transforms: Towards Precise Code Rewriting using LLMs
Chris Cummins, Volker Seeker, Jordi Armengol-Estapé +3
Tools for rewriting, refactoring and optimizing code should be fast and correct. Large language models (LLMs), by their nature, possess neither of these qualities. Yet, there remai…
Meta Large Language Model Compiler: Foundation Models of Compiler Optimization
Chris Cummins, Volker Seeker, Dejan Grubisic +4
Large Language Models (LLMs) have demonstrated remarkable capabilities across a variety of software engineering and coding tasks. However, their application in the domain of code a…
LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers
Massinissa Merouani, Afif Boudaoud, Iheb Nassim Aouadj +7
While polyhedral compilers have shown success in implementing advanced code transformations, they still face challenges in selecting the ones that lead to the most profitable speed…
CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution
Alex Gu, Baptiste Rozière, Hugh Leather +3
We present CRUXEval (Code Reasoning, Understanding, and eXecution Evaluation), a benchmark consisting of 800 Python functions (3-13 lines). Each function comes with an input-output…
Sieve: Multimodal Dataset Pruning Using Image Captioning Models
Anas Mahmoud, Mostafa Elhoushi, Amro Abbas +4
Vision-Language Models (VLMs) are pretrained on large, diverse, and noisy web-crawled datasets. This underscores the critical need for dataset pruning, as the quality of these data…