6 papers
RoLaQ: Joint Rotation and Range Calibration for 2-Bit KV Caches in Multi-Head Latent Attention
Shiyu Ji, Peng Ling, Chen Lin +4
Multi-head latent attention (MLA) compresses the content of a key-value cache into a shared latent per token, making low-bit storage attractive for long-context inference. At two b…
SWE-Hub: A Unified Production System for Scalable, Executable Software Engineering Tasks
Yucheng Zeng, Shupeng Li, Daxiang Dong +11
Progress in software-engineering agents is increasingly constrained by the scarcity of executable, scalable, and realistic data for training and evaluation. This scarcity stems fro…
LOGIGEN: Logic-Driven Generation of Verifiable Agentic Tasks
Yucheng Zeng, Weipeng Lu, Linyun Liu +9
The evolution of Large Language Models (LLMs) from static instruction-followers to autonomous agents necessitates operating within complex, stateful environments to achieve precise…
QianfanHuijin Technical Report: A Novel Multi-Stage Training Paradigm for Finance Industrial LLMs
Shupeng Li, Weipeng Lu, Linyun Liu +16
Domain-specific enhancement of Large Language Models (LLMs) within the financial context has long been a focal point of industrial application. While previous models such as Bloomb…
Qianfan-VL: Domain-Enhanced Universal Vision-Language Models
Daxiang Dong, Mingming Zheng, Dong Xu +32
We present Qianfan-VL, a series of multimodal large language models ranging from 3B to 70B parameters, achieving state-of-the-art performance through innovative domain enhancement…
Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features
Qingrui Jia, Xuhong Li, Lei Yu +5
While mislabeled or ambiguously-labeled samples in the training set could negatively affect the performance of deep models, diagnosing the dataset and identifying mislabeled sample…