activity
20222026
most citedA Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering

30 citations · 40 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CL2026

Efficient RAG with Intent-Aware Retrieval and Semantics-Preserving Chunking

Fachrina Dewi Puspitasari, Chaoning Zhang, Jiaquan Zhang +6

The demand for powerful instruction following and reasoning capability of large language models (LLMs) has promoted rapid development of retrieval-augmented generation (RAG). The R…

cs.CL2026

Small Language Model Helps Resolve Semantic Ambiguity of LLM Prompt

Zhenzhen Huang, Chaoning Zhang, Fachrina Dewi Puspitasari +4

Large language models (LLMs) are increasingly utilized in various complex reasoning tasks due to their excellent instruction following capability. However, the model's performance…

cs.NE2026

Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models

Xudong Wang, Chaoning Zhang, Chenghao Li +10

Large Language Models (LLMs) have demonstrated strong capabilities in complex reasoning tasks, while recent prompting strategies such as Chain-of-Thought (CoT) have further elevate…

cs.LG2026

Geometric Neural Operators via Lie Group-Constrained Latent Dynamics

Jiaquan Zhang, Fachrina Dewi Puspitasari, Songbo Zhang +7

Neural operators offer an effective framework for learning solutions of partial differential equations for many physical systems in a resolution-invariant and data-driven manner. E…

cs.CL2026

Text summarization via global structure awareness

Jiaquan Zhang, Chaoning Zhang, Shuxu Chen +9

Text summarization is a fundamental task in natural language processing (NLP), and the information explosion has made long-document processing increasingly demanding, making summar…

cs.CV2025

Fast SAM2 with Text-Driven Token Pruning

Avilasha Mandal, Chaoning Zhang, Fachrina Dewi Puspitasari +6

Segment Anything Model 2 (SAM2), a vision foundation model has significantly advanced in prompt-driven video object segmentation, yet their practical deployment remains limited by…

cs.CV2025

Exploring Kernel Transformations for Implicit Neural Representations

Sheng Zheng, Chaoning Zhang, Dongshen Han +4

Implicit neural representations (INRs), which leverage neural networks to represent signals by mapping coordinates to their corresponding attributes, have garnered significant atte…

cs.AI2024★ 10 cited

Sora as a World Model? A Complete Survey on Text-to-Video Generation

Fachrina Dewi Puspitasari, Chaoning Zhang, Joseph Cho +13

The evolution of video generation from text, from animating MNIST to simulating the world with Sora, has progressed at a breakneck speed. Here, we systematically discuss how far te…

cs.CY2023

Ghost Booking as a New Philanthropy Channel: A Case Study on Ukraine-Russia Conflict

Fachrina Dewi Puspitasari, Gareth Tyson, Ehsan-Ul Haq +2

The term ghost booking has recently emerged as a new way to conduct humanitarian acts during the conflict between Russia and Ukraine in 2022. The phenomenon describes the events wh…

cs.CV2023★ 30 cited

A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering

Chaoning Zhang, Joseph Cho, Fachrina Dewi Puspitasari +11

The Segment Anything Model (SAM), developed by Meta AI Research, represents a significant breakthrough in computer vision, offering a robust framework for image and video segmentat…

cs.HC2022

Review of Persuasive User Interface as Strategy for Technology Addiction in Virtual Environments

Fachrina Dewi Puspitasari, Lik-Hang Lee

In the era of virtuality, the increasingly ubiquitous technology bears the challenge of excessive user dependency, also known as user addiction. Augmented reality (AR) and virtual…