|
Austria-Di-Di Azienda Directories
|
Azienda News:
- LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in . . .
Recent reports claim that large language models (LLMs) now outperform elite humans in competitive programming Drawing on knowledge from a group of medalists in international algorithmic contests, we revisit this claim, examining how LLMs differ from human experts and where limitations still remain
- It is clear that the state-of-the-art large-scale language . . .
There are reports that LLMs outperform human competitive programmers in competitive programming AI researchers who were skeptical of this have built a benchmark called ' LiveCodeBench Pro '
- [2404. 10952] Can Language Models Solve Olympiad Programming?
In this paper, we introduce the USACO benchmark with 307 problems from the USA Computing Olympiad, along with high-quality unit tests, reference code, and official analyses for each problem These resources enable us to construct and test a range of LM inference methods for competitive programming for the first time
- How Do Olympiad Medalists Judge LLMs in Competitive . . .
A new benchmark assembled by a team of International Olympiad medalists suggests the hype about large language models beating elite human coders is premature LiveCodeBench Pro, unveiled in a 584-problem study [PDF] drawn from Codeforces, ICPC and IOI contests, shows the best frontier model clears j
- 2025년 6월 16일 - by Kim Seonghyeon - arXiv Daily
Recent reports claim that large language models (LLMs) now outperform elite humans in competitive programming Drawing on knowledge from a group of medalists in international algorithmic contests, we revisit this claim, examining how LLMs differ from human experts and where limitations still remain
- Competitive Programming with Large Reasoning Models
We show that reinforcement learning applied to large language models (LLMs) significantly boosts performance on complex coding and reasoning tasks
- Evaluating Language Models in Programming Competitions
This competition is well-known in Romania, which has a strong history in computer science contests The study uses a collection of 304 programming challenges from the years 2002 to 2023, focusing on problems written in C++ and Python #Goals of the Study The main goal is to find out why LLMs do well or poorly on different types of programming
|
|