most citedInfant Agent: A Tool-Integrated, Logic-Driven Agent with Cost-Effective API Usage

1 citations · 1 across the 4 of their papers we have counts for

collaborators

12 papers

cs.IR2025

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…

cs.CV2025

Optimizing Multi-Round Enhanced Training in Diffusion Models for Improved Preference Understanding

Kun Li, Jianhui Wang, Yangfan He +10

Generative AI has significantly changed industries by enabling text-driven image generation, yet challenges remain in achieving high-resolution outputs that align with fine-grained…

cs.AI2025

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…

cs.CL2025

SCORE: Story Coherence and Retrieval Enhancement for AI Narratives

Qiang Yi, Yangfan He, Jianhui Wang +18

Large Language Models (LLMs) can generate creative and engaging narratives from user-specified input, but maintaining coherence and emotional depth throughout these AI-generated st…

cs.CV2025

TDRI: Two-Phase Dialogue Refinement and Co-Adaptation for Interactive Image Generation

Yuheng Feng, Jianhui Wang, Kun Li +5

Although text-to-image generation technologies have made significant advancements, they still face challenges when dealing with ambiguous prompts and aligning outputs with user int…

cs.CV2025

A Cascading Cooperative Multi-agent Framework for On-ramp Merging Control Integrating Large Language Models

Miao Zhang, Zhenlong Fang, Tianyi Wang +4

Traditional Reinforcement Learning (RL) suffers from replicating human-like behaviors, generalizing effectively in multi-agent scenarios, and overcoming inherent interpretability i…