6 papers
GTA-2: Benchmarking General Tool Agents from Atomic Tool-Use to Open-Ended Workflows
Jize Wang, Xuanxuan Liu, Yining Li +7
The development of general-purpose agents requires a shift from executing simple instructions to completing complex, real-world productivity workflows. However, current tool-use be…
RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents
Jize Wang, Han Wu, Zhiyuan You +9
Mixture-of-Agents (MoA) improves LLM performance through layered collaboration, but its dense topology raises costs and latency. Existing methods employ LLM judges to filter respon…
CAD-GPT: Synthesising CAD Construction Sequence with Spatial Reasoning-Enhanced Multimodal LLMs
Siyu Wang, Cailian Chen, Xinyi Le +4
Computer-aided design (CAD) significantly enhances the efficiency, accuracy, and innovation of design processes by enabling precise 2D and 3D modeling, extensive analysis, and opti…
Reviving DSP for Advanced Theorem Proving in the Era of Reasoning Models
Chenrui Cao, Liangcheng Song, Zenan Li +4
Recent advancements, such as DeepSeek-Prover-V2-671B and Kimina-Prover-Preview-72B, demonstrate a prevailing trend in leveraging reinforcement learning (RL)-based large-scale train…
SAIL: Sample-Centric In-Context Learning for Document Information Extraction
Jinyu Zhang, Zhiyuan You, Jize Wang +1
Document Information Extraction (DIE) aims to extract structured information from Visually Rich Documents (VRDs). Previous full-training approaches have demonstrated strong perform…
GTA: A Benchmark for General Tool Agents
Jize Wang, Zerun Ma, Yining Li +4
Significant focus has been placed on integrating large language models (LLMs) with various tools in developing general-purpose agents. This poses a challenge to LLMs' tool-use capa…