2 citations · 2 across the 11 of their papers we have counts for
11 papers
ComfySearch: Autonomous Exploration and Reasoning for ComfyUI Workflows
Jinwei Su, Qizhen Lan, Zeyu Wang +7
AI-generated content has progressed from monolithic models to modular workflows, especially on platforms like ComfyUI, allowing users to customize complex creative pipelines. Howev…
MAPGD: Multi-Agent Prompt Gradient Descent for Collaborative Prompt Optimization
Yichen Han, Yuhang Han, Siteng Huang +7
Prompt engineering is crucial for fully leveraging large language models (LLMs), yet most existing optimization methods follow a single trajectory, resulting in limited adaptabilit…
Difficulty-Aware Agentic Orchestration for Query-Specific Multi-Agent Workflows
Jinwei Su, Qizhen Lan, Yinghui Xia +6
Large Language Model (LLM)-based agentic systems have shown strong capabilities across various tasks. However, existing multi-agent frameworks often rely on static or task-level wo…
NaturalGAIA: A Verifiable Benchmark and Hierarchical Framework for Long-Horizon GUI Tasks
Zihan Zheng, Tianle Cui, Taoran Wang +4
Despite significant advances in LLM-driven GUI agents, the field remains constrained by the challenge of reconciling high-fidelity realism with verifiable evaluation accuracy. To a…
THOR: Transformer Heuristics for On-Demand Retrieval
Isaac Shi, Zeyuan Li, Fan Liu +4
We introduce the THOR (Transformer Heuristics for On-Demand Retrieval) Module, designed and implemented by eSapiens, a secure, scalable engine that transforms natural-language ques…
eSapiens's DEREK Module: Deep Extraction & Reasoning Engine for Knowledge with LLMs
Isaac Shi, Zeyuan Li, Fan Liu +4
We present the DEREK (Deep Extraction & Reasoning Engine for Knowledge) Module, a secure and scalable Retrieval-Augmented Generation pipeline designed specifically for enterprise d…
eSapiens: A Platform for Secure and Auditable Retrieval-Augmented Generation
Isaac Shi, Zeyuan Li, Fan Liu +4
We present eSapiens, an AI-as-a-Service (AIaaS) platform engineered around a business-oriented trifecta: proprietary data, operational workflows, and any major agnostic Large Langu…
eSapiens: A Real-World NLP Framework for Multimodal Document Understanding and Enterprise Knowledge Processing
Isaac Shi, Zeyuan Li, Wenli Wang +3
We introduce eSapiens, a unified question-answering system designed for enterprise settings, which bridges structured databases and unstructured textual corpora via a dual-module a…
DebFlow: Automating Agent Creation via Agent Debate
Jinwei Su, Yinghui Xia, Yiqun Duan +4
Large language models (LLMs) have demonstrated strong potential and impressive performance in automating the generation and optimization of workflows. However, existing approaches…
Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey
Junqiao Wang, Zeng Zhang, Yangfan He +18
With the rapid evolution of large language models (LLM), reinforcement learning (RL) has emerged as a pivotal technique for code generation and optimization in various domains. Thi…
FALCON: Feedback-driven Adaptive Long/short-term memory reinforced Coding Optimization system
Zeyuan Li, Yangfan He, Lewei He +5
Recently, large language models (LLMs) have achieved significant progress in automated code generation. Despite their strong instruction-following capabilities, these models freque…