Llms Ai Startups

[P] LLM with a 9-line seed + 5 rounds of contrastive feedback outperforms Optuna on 96% of benchmarks

Reddit - Machine Learning March 30, 2026 1 min read

About this article

submitted by /u/se4u [link] [comments]

You've been blocked by network security.To continue, log in to your Reddit account or use your developer tokenIf you think you've been blocked by mistake, file a ticket below and we'll look into it.Log in File a ticket

Originally published on March 30, 2026. Curated by AI News.

Read Original Article

Llms

[2603.16629] MLLM-based Textual Explanations for Face Comparison

Abstract page for arXiv paper 2603.16629: MLLM-based Textual Explanations for Face Comparison

arXiv - AI · 4 min · 7 minutes ago

Llms

[2603.15159] To See is Not to Master: Teaching LLMs to Use Private Libraries for Code Generation

Abstract page for arXiv paper 2603.15159: To See is Not to Master: Teaching LLMs to Use Private Libraries for Code Generation

arXiv - AI · 4 min · 7 minutes ago

Llms

[2602.08316] SWE Context Bench: A Benchmark for Context Learning in Coding

Abstract page for arXiv paper 2602.08316: SWE Context Bench: A Benchmark for Context Learning in Coding

arXiv - AI · 4 min · 7 minutes ago

Llms

[2601.13227] Insider Knowledge: How Much Can RAG Systems Gain from Evaluation Secrets?

Abstract page for arXiv paper 2601.13227: Insider Knowledge: How Much Can RAG Systems Gain from Evaluation Secrets?

[P] LLM with a 9-line seed + 5 rounds of contrastive feedback outperforms Optuna on 96% of benchmarks

About this article

Related Articles

[2603.16629] MLLM-based Textual Explanations for Face Comparison

[2603.15159] To See is Not to Master: Teaching LLMs to Use Private Libraries for Code Generation

[2602.08316] SWE Context Bench: A Benchmark for Context Learning in Coding

[2601.13227] Insider Knowledge: How Much Can RAG Systems Gain from Evaluation Secrets?

No comments

Stay updated with AI News