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cs.CL2026

PI-Mem: Pushing Long-Context Reasoning to 3.6M Tokens with Parallel-Iterative Memory

Dawei Liu, Haixu Song, Shuang Cheng +9

Long-context reasoning remains a critical bottleneck for large language models, as recent recurrent-memory approaches face two inherent challenges: sequential chunk-wise updates ca…

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

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…

cs.CL2025

DePass: Unified Feature Attributing by Simple Decomposed Forward Pass

Xiangyu Hong, Che Jiang, Kai Tian +4

Attributing the behavior of Transformer models to internal computations is a central challenge in mechanistic interpretability. We introduce DePass, a unified framework for feature…