3 papers
cs.CL2026
DEdit: Iterative Draft Editing for Speculative Decoding
Longxuan Yu, Bingsen Chen, Peng Shi +9
Speculative decoding accelerates autoregressive LLMs by having a lightweight drafter propose tokens that the target model verifies in parallel. Diffusion-based drafters further red…
cs.AI2025
DSMentor: Enhancing Data Science Agents with Curriculum Learning and Online Knowledge Accumulation
He Wang, Alexander Hanbo Li, Yiqun Hu +6
Large language model (LLM) agents have shown promising performance in generating code for solving complex data science problems. Recent studies primarily focus on enhancing in-cont…
cs.CL2025
What Really Matters for Table LLMs? A Meta-Evaluation of Model and Data Effects
Naihao Deng, Sheng Zhang, Henghui Zhu +7
Table modeling has progressed for decades. In this work, we revisit this trajectory and highlight emerging challenges in the LLM era, particularly the paradox of choice: the diffic…