9 papers
TACO: Tool-Augmented Credit Optimization for Agentic Tool Use
Mingkuan Feng, Jinyang Wu, Hao Gu +5
Agentic multimodal models perform diverse operations on an image via code and reason over the returned view, an effective paradigm for fine-grained visual question answering. Howev…
Atlas: Orchestrating Heterogeneous Models and Tools for Multi-Domain Complex Reasoning
Jinyang Wu, Guocheng Zhai, Ruihan Jin +5
The integration of large language models (LLMs) with external tools has significantly expanded the capabilities of AI agents. However, as the diversity of both LLMs and tools incre…
Maestro: Reinforcement Learning to Orchestrate Hierarchical Model-Skill Ensembles
Jinyang Wu, Guocheng Zhai, Ruihan Jin +7
The proliferation of large language models (LLMs) and modular skills has endowed autonomous agents with increasingly powerful capabilities. Existing frameworks typically rely on mo…
Two-Stage Regularization-Based Structured Pruning for LLMs
Mingkuan Feng, Jinyang Wu, Siyuan Liu +7
The deployment of large language models (LLMs) is largely hindered by their large number of parameters. Structural pruning has emerged as a promising solution. Prior structured pru…
Exploring Knowledge Purification in Multi-Teacher Knowledge Distillation for LLMs
Ruihan Jin, Pengpeng Shao, Zhengqi Wen +5
Knowledge distillation has emerged as a pivotal technique for transferring knowledge from stronger large language models (LLMs) to smaller, more efficient models. However, traditio…
AStar: Boosting Multimodal Reasoning with Automated Structured Thinking
Jinyang Wu, Mingkuan Feng, Guocheng Zhai +7
Multimodal large language models excel across diverse domains but struggle with complex visual reasoning tasks. To enhance their reasoning capabilities, current approaches typicall…