12 papers
Thinking Seeds: Leveraging Historical Diversity for Position-Aware RL in LLMs
Lei Yang, Wei Bi, Chenxi Sun +2
On-policy reinforcement learning (RL) for language model post-training suffers from a fundamental tension: as training progresses, policy entropy collapses and sampling diversity d…
Evaluating the Generation Capabilities of Large Chinese Language Models
Hui Zeng, Jingyuan Xue, Meng Hao +3
This paper unveils CG-Eval, the first-ever comprehensive and automated evaluation framework designed for assessing the generative capabilities of large Chinese language models acro…
WarmServe: Enabling One-for-Many GPU Prewarming for Multi-LLM Serving
Chiheng Lou, Sheng Qi, Rui Kang +5
Deploying multiple models within shared GPU clusters is a key strategy to improve resource efficiency in large language model (LLM) serving. Existing multi-LLM serving systems impr…
Beyond Quantity: Trajectory Diversity Scaling for Code Agents
Guhong Chen, Chenghao Sun, Cheng Fu +16
As code large language models (LLMs) evolve into tool-interactive agents via the Model Context Protocol (MCP), their generalization is increasingly limited by low-quality synthetic…
Compass-Embedding v4: Robust Contrastive Learning for Multilingual E-commerce Embeddings
Pakorn Ueareeworakul, Shuman Liu, Jinghao Feng +7
As global e-commerce rapidly expands into emerging markets, the lack of high-quality semantic representations for low-resource languages has become a decisive bottleneck for retrie…
You May Speak Freely: Improving the Fine-Grained Visual Recognition Capabilities of Multimodal Large Language Models with Answer Extraction
Logan Lawrence, Oindrila Saha, Megan Wei +3
Despite the renewed interest in zero-shot visual classification due to the rise of Multimodal Large Language Models (MLLMs), the problem of evaluating free-form responses of auto-r…