activity
20242026
most citedA Survey on Large Language Model-Based Game Agents

6 citations · 6 across the 3 of their papers we have counts for

collaborators

17 papers

cs.AI20266 cited

A Survey on Large Language Model-Based Game Agents

Sihao Hu, Tiansheng Huang, Gaowen Liu +6

Game environments provide rich, controllable settings that stimulate many aspects of real-world complexity. As such, game agents offer a valuable testbed for exploring capabilities…

cs.CR2026

MELT: A Behavioral Trace Dataset for High-Risk Memecoin Launch Detection

Sihao Hu, Selim Furkan Tekin, Yichang Xu +1

Launchpads have become the dominant mechanism for issuing memecoins, exposing investors to a new class of high-risk launches that existing rug-pull detection methods cannot capture…

cs.CV2026

Personalized Face Privacy Protection From a Single Image

Zachary Yahn, Fatih Ilhan, Tiansheng Huang +5

Photos of faces uploaded online are vulnerable to malicious actors who can scrape facial images from online sources and intrude on personal privacy via unauthorized use of facial r…

cs.CR2026

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey

Tiansheng Huang, Sihao Hu, Fatih Ilhan +2

Recent research demonstrates that the nascent fine-tuning-as-a-service business model exposes serious safety concerns: fine-tuning with a few harmful data uploaded from the users c…

cs.CV2026

Attention-aware Inference Optimizations for Large Vision-Language Models with Memory-efficient Decoding

Fatih Ilhan, Gaowen Liu, Ramana Rao Kompella +5

Large Vision-Language Models (VLMs) have achieved remarkable success in multi-modal reasoning, but their inference time efficiency remains a significant challenge due to the memory…

cs.CV2026

A Multi-Agent Perception-Action Alliance for Efficient Long Video Reasoning

Yichang Xu, Gaowen Liu, Ramana Rao Kompella +6

This paper presents a multi-agent perception-action exploration alliance, dubbed A4VL, for efficient long-video reasoning. A4VL operates in a multi-round perception-action explorat…