25 citations · 41 across the 10 of their papers we have counts for
11 papers
SuperMemory-VQA: An Egocentric Visual Question-Answering Benchmark for Long-Horizon Memory
Samiul Alam, Shakhrul Iman Siam, Michael J. Proulx +4
AI glasses present a compelling platform for AI agents to serve as personalized memory assistants. To be genuinely useful, such systems must move beyond short-term video comprehens…
SkillEvolBench: Benchmarking the Evolution from Episodic Experience to Procedural Skills
Yingtie Lei, Zhongwei Wan, Jiankun Zhang +13
Large language model (LLM) agents accumulate rich episodic trajectories while solving real-world tasks, but it remains unclear whether such experience can be distilled into reusabl…
MMDeepResearch-Bench: A Benchmark for Multimodal Deep Research Agents
Peizhou Huang, Zixuan Zhong, Zhongwei Wan +12
Deep Research Agents (DRAs) generate citation-rich reports via multi-step search and synthesis, yet existing benchmarks mainly target text-only settings or short-form multimodal QA…
Benchmarking is Broken -- Don't Let AI be its Own Judge
Zerui Cheng, Stella Wohnig, Ruchika Gupta +13
The meteoric rise of AI, with its rapidly expanding market capitalization, presents both transformative opportunities and critical challenges. Chief among these is the urgent need…
Reading Recognition in the Wild
Charig Yang, Samiul Alam, Shakhrul Iman Siam +12
To enable egocentric contextual AI in always-on smart glasses, it is crucial to be able to keep a record of the user's interactions with the world, including during reading. In thi…
SVD-LLM V2: Optimizing Singular Value Truncation for Large Language Model Compression
Xin Wang, Samiul Alam, Zhongwei Wan +2
Despite significant advancements, the practical deployment of Large Language Models (LLMs) is often hampered by their immense sizes, highlighting the need for effective compression…
The Internet of Things in the Era of Generative AI: Vision and Challenges
Xin Wang, Zhongwei Wan, Arvin Hekmati +4
Advancements in Generative AI hold immense promise to push Internet of Things (IoT) to the next level. In this article, we share our vision on IoT in the era of Generative AI. We d…
Efficient Large Language Models: A Survey
Zhongwei Wan, Xin Wang, Che Liu +9
Large Language Models (LLMs) have demonstrated remarkable capabilities in important tasks such as natural language understanding and language generation, and thus have the potentia…
FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things
Samiul Alam, Tuo Zhang, Tiantian Feng +8
There is a significant relevance of federated learning (FL) in the realm of Artificial Intelligence of Things (AIoT). However, most existing FL works do not use datasets collected…
GPT-FL: Generative Pre-trained Model-Assisted Federated Learning
Tuo Zhang, Tiantian Feng, Samiul Alam +5
In this work, we propose GPT-FL, a generative pre-trained model-assisted federated learning (FL) framework. At its core, GPT-FL leverages generative pre-trained models to generate…
FedAudio: A Federated Learning Benchmark for Audio Tasks
Tuo Zhang, Tiantian Feng, Samiul Alam +4
Federated learning (FL) has gained substantial attention in recent years due to the data privacy concerns related to the pervasiveness of consumer devices that continuously collect…