From the 1 of 11 linked papers with an AI index.
11 papers
Ring-Zero: Scaling Zero RL to a Trillion Parameters for Emergent Reasoning
Xinyu Tang, Qianggang Cao, Yurou Liu +13
The paper introduces a training pipeline that scales zero‑reinforcement‑learning to a trillion‑parameter language model, revealing emergent chain‑of‑thought reasoning abilities and…
ForesightKV: Optimizing KV Cache Eviction for Reasoning Models by Learning Long-Term Contribution
Zican Dong, Peiyu Liu, Junyi Li +4
Recently, large language models (LLMs) have shown remarkable reasoning abilities by producing long reasoning traces. However, as the sequence length grows, the key-value (KV) cache…
A Survey of Large Language Models
Wayne Xin Zhao, Kun Zhou, Junyi Li +19
Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for compre…
How Efficient Are Diffusion Language Models? A Critical Examination of Efficiency Evaluation Practices
Han Peng, Peiyu Liu, Zican Dong +5
Diffusion language models (DLMs) have emerged as a promising alternative to the long-dominant autoregressive (AR) paradigm, offering a parallelable decoding process that could yiel…
Sticker-TTS: Learn to Utilize Historical Experience with a Sticker-driven Test-Time Scaling Framework
Jie Chen, Jinhao Jiang, Yingqian Min +4
Large reasoning models (LRMs) have exhibited strong performance on complex reasoning tasks, with further gains achievable through increased computational budgets at inference. Howe…
InvestAlign: Overcoming Data Scarcity in Aligning Large Language Models with Investor Decision-Making Processes under Herd Behavior
Huisheng Wang, Zhuoshi Pan, Hangjing Zhang +3
Aligning Large Language Models (LLMs) with investor decision-making processes under herd behavior is a critical challenge in behavioral finance, which grapples with a fundamental l…