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cs.CL2026

SimpleOPD: Simple Tokenizer-Agnostic On-Policy Distillation for Long-Context Reasoning

Haonan He, Haodi Lei, Yun Luo +13

On-policy distillation (OPD) offers a promising way to transfer reasoning capabilities from stronger teacher models, but applying it to long-context reasoning teachers and short-co…

cs.CL2026

Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering

Junlin Yang, Che Jiang, Yu Fu +21

The paper presents Frontis-MA1, a 35‑billion‑parameter model trained as a meta‑evolution agent for machine learning engineering, using a new OpenMLE stack that combines operator le…

cs.CL2026

Draft-OPD: On-Policy Distillation for Speculative Draft Models

Haodi Lei, Yafu Li, Haoran Zhang +8

Speculative decoding accelerates large language model inference by pairing a target model with a lightweight draft model whose proposed tokens are verified in parallel. A common wa…

cs.CL2026

Teaching Thinking Models to Reason with Tools: A Full-Pipeline Recipe for Tool-Integrated Reasoning

Qianjia Cheng, Yuchen Zhang, Zhilin Wang +9

Tool-integrated reasoning (TIR) offers a direct way to extend thinking models beyond the limits of text-only reasoning. Paradoxically, we observe that tool-enabled evaluation can d…

cs.CL2026

LFQA-E: Carefully Benchmarking Long-form QA Evaluation

Yuchen Fan, Chen Lin, Xin Zhong +11

Long-Form Question Answering (LFQA) involves generating comprehensive, paragraph-level responses to open-ended questions, which poses a significant challenge for evaluation due to…

cs.CL2026

EVA-Score: Evaluating Abstractive Long-form Summarization on Informativeness through Extraction and Validation

Yuchen Fan, Yazhe Wan, Xin Zhong +3

Since LLMs emerged, more attention has been paid to abstractive long-form summarization, where longer input sequences indicate more information contained. Nevertheless, the automat…