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Ting-Ting Yu

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#artificial intelligence Preprint Sep 2026

Beyond Token Scale: Chunk-Level Sparse Autoencoders for Reliable Semantic Feature Discovery

A family of chunk-level SAEs that encode mean-pooled activations over chunks, each a contiguous span of tokens: Mean-Chunk reconstructs the observed chunk, Cross-Chunk predicts an independently processed neighbor, and Joint-Chunk combines both targets are introduced.

Xu Wang, Yi-Fan Yang, Ting-Ting Yu et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Hunyuan-A13B Technical Report

We present Hunyuan-A13B, an open-source large language model based on a Mixture-of-Experts architecture. It contains 80 billion total parameters but activates only 13 billion during inference, balancing model capability, computational efficiency, and deployment cost. The model is pretrained on a rigorously filtered 20T...

Tencent Hunyuan Team, Ao Liu, Bo Zhou et al. · 0 citations
#artificial intelligence Review Sep 2026

Environment Evolution for Terminal Agents

This paper proposes environment evolution, which incrementally increases environment difficulty off-policy and schedules the evolved environments generation by generation during training to provide continuous learning signals.

Zhi-Yuan Fan, Ting-Ting Yu, Yu-Tong Cai et al. · 2 citations
Preprint Aug 2026

Deep Research Pretraining via Predictive Navigation

Deep Research Pretraining (DRP), an offline framework that derives predictive navigation supervision from naturally occurring evidence structures, is introduced, an offline framework that derives predictive navigation supervision from naturally occurring evidence structures.

Jiang-Nan Zhou, Zhi-Yuan Fan, Xing Wu et al. · 2 citations
Preprint Aug 2026

DocPO: Advancing Document Policy Optimization via Tailored Step-Aware Rewards

This work proposes Step-Aware Annealing (SAA), a plug-and-play reward sharpening mechanism that progressively increases reward curvature during training, amplifying subtle quality differences among high-scoring samples while preserving stability in early learning.

Yunhao Wang, Bing-Hong Wu, Zhenyu Huang et al. · 0 citations

PolicyLong: Towards On-Policy Context Extension

PolicyLong is proposed, shifting data construction towards a dynamic on-policy paradigm, by iteratively re-executing data screening (entropy computation, retrieval, and verification) using the current model, which ensures the training distribution tracks evolving capabilities, yielding an emergent self-curriculum.

Junlong Jia, Jiangnan Zhou, Ziyang Chen et al. · 0 citations
Preprint Jul 2026

MORE: A Multilingual Document Parsing Benchmark and Evaluation

Multilingual documents encapsulate rich regional cultures, scientific discoveries, and historical records. Parsing this content into structured, machine-readable formats is critical for unlocking global knowledge. However, existing benchmarks predominantly focus on high-resource languages like English and Chinese, crea...

Long Xu, Binghong Wu, Ting-Ting Yu et al. · 3 citations

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