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arXiv preprint arXiv:2402.02172 , year=

4 Pith papers cite this work. Polarity classification is still indexing.

4 Pith papers citing it

years

2026 3 2025 1

representative citing papers

Delta-Based Neural Architecture Search: LLM Fine-Tuning via Code Diffs

cs.LG · 2026-05-06 · unverdicted · novelty 7.0

Fine-tuned 7B LLMs generating unified diffs for neural architecture refinement achieve 66-75% valid rates and 64-66% mean first-epoch accuracy, outperforming full-generation baselines by large margins while cutting output length by 75-85%.

Memory in the Age of AI Agents

cs.CL · 2025-12-15 · unverdicted · novelty 6.0

The paper maps agent memory research via three forms (token-level, parametric, latent), three functions (factual, experiential, working), and dynamics of formation/evolution/retrieval, plus benchmarks and future directions.

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Showing 4 of 4 citing papers.

  • Delta-Based Neural Architecture Search: LLM Fine-Tuning via Code Diffs cs.LG · 2026-05-06 · unverdicted · none · ref 32

    Fine-tuned 7B LLMs generating unified diffs for neural architecture refinement achieve 66-75% valid rates and 64-66% mean first-epoch accuracy, outperforming full-generation baselines by large margins while cutting output length by 75-85%.

  • Towards Personalizing Secure Programming Education with LLM-Injected Vulnerabilities cs.CR · 2026-04-15 · conditional · none · ref 26

    LLM agents inject CWEs into student-authored code to generate personalized security examples; in a 71-student deployment, participants rated them more relevant than textbook cases but quantitative differences remained limited.

  • XSearch: Explainable Code Search via Concept-to-Code Alignment cs.SE · 2026-05-15 · unverdicted · none · ref 77

    XSearch achieves explainable code search by breaking queries into functional concepts and matching them directly to code statements, delivering large gains on out-of-distribution benchmarks.

  • Memory in the Age of AI Agents cs.CL · 2025-12-15 · unverdicted · none · ref 227

    The paper maps agent memory research via three forms (token-level, parametric, latent), three functions (factual, experiential, working), and dynamics of formation/evolution/retrieval, plus benchmarks and future directions.