mlsanityData to 14 Oct 2026

Can Low-Rank Knowledge Distillation in LLMs be Useful for Microelectronic Reasoning?

arXiv 2406.13808 ↗First posted 19 Jun 2024cs.LGcited by 1

On the map: LLM reasoning → Reasoning benchmarks and evaluation

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Abstract (arXiv)

In this work, we present empirical results regarding the feasibility of using offline large language models (LLMs) in the context of electronic design automation (EDA). The goal is to investigate and evaluate a contemporary language model's (Llama-2-7B) ability to function as a microelectronic Q & A expert as well as its reasoning, and generation capabilities in solving microelectronic-related problems. Llama-2-7B was tested across a variety of adaptation methods, including introducing a novel low-rank knowledge distillation (LoRA-KD) scheme. Our experiments produce both qualitative and quantitative results.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 6 of its 21 references that are in the map. First posted on arXiv 19 Jun 2024.

Builds on

6 of 21 references.

References · 6

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2023GPT-4 Technical Reportcited by 18,396
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  4. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  5. 2019DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lightercited by 4,307
  6. 2019Patient Knowledge Distillation for BERT Model Compressioncited by 508

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Can an Actor-Critic Optimization Framework Improve Analog Design?cited by 1

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  1. 2026RF-Agent: A Practical Framework for Building Language Agents for RFIC Design
  2. 2025Large Language Models (LLMs) for Electronic Design Automation (EDA)
  3. 2026CircuitLM: A Multi-Agent LLM-Aided Design Framework for Generating Circuit Schematics from Natural Language Prompts
  4. 2025MMCircuitEval: A Comprehensive Multimodal Circuit-Focused Benchmark for Evaluating LLMs
  5. 2025CIRCUIT: A Benchmark for Circuit Interpretation and Reasoning Capabilities of LLMs
  6. 2026ChipLingo: A Systematic Training Framework for Large Language Models in EDA
  7. 2025EngiBench: A Benchmark for Evaluating Large Language Models on Engineering Problem Solving
  8. 2026LLM for EDA in Front-End Design: Challenges and Opportunities