7 papers
SimSD: Simple Speculative Decoding in Diffusion Language Models
Junxia Cui, Haotian Ye, Runchu Tian +9
Diffusion large language models (dLLMs) have recently emerged as a promising alternative to autoregressive (AR) LLMs, offering faster inference through parallel or blockwise decodi…
ChipMATE: Multi-Agent Training via Reinforcement Learning for Enhanced RTL Generation
Zhongkai Yu, Yichen Lin, Chenyang Zhou +12
Existing API-based agentic systems for RTL code generation are fundamentally misaligned with industrial practice: they assume a golden testbench is available at generation time, re…
EvoLen: Evolution-Guided Tokenization for DNA Language Model
Nan Huang, Xiaoxiao Zhou, Junxia Cui +4
Tokens serve as the basic units of representation in DNA language models (DNALMs), yet their design remains underexplored. Unlike natural language, DNA lacks inherent token boundar…
Steer2Adapt: Dynamically Composing Steering Vectors Elicits Efficient Adaptation of LLMs
Pengrui Han, Xueqiang Xu, Keyang Xuan +12
Activation steering has emerged as a promising approach for efficiently adapting large language models (LLMs) to downstream behaviors. However, most existing steering methods rely…
ChipBench: A Next-Step Benchmark for Evaluating LLM Performance in AI-Aided Chip Design
Zhongkai Yu, Chenyang Zhou, Yichen Lin +6
While Large Language Models (LLMs) show significant potential in hardware engineering, current benchmarks suffer from saturation and limited task diversity, failing to reflect LLMs…
Finish First, Perfect Later: Test-Time Token-Level Cross-Validation for Diffusion Large Language Models
Runchu Tian, Junxia Cui, Xueqiang Xu +2
Diffusion large language models (dLLMs) have recently emerged as a promising alternative to autoregressive (AR) models, offering advantages such as accelerated parallel decoding an…