178 citations · 195 across the 14 of their papers we have counts for
7 papers · 1 filter
EffGen: Enabling Small Language Models as Capable Autonomous Agents
Gaurav Srivastava, Aafiya Hussain, Chi Wang +2
Most existing language model agentic systems today are built and optimized for large language models (e.g., GPT, Claude, Gemini) via API calls; while powerful, this approach faces…
Prompt-Induced Linguistic Fingerprints for LLM-Generated Fake News Detection
Chi Wang, Min Gao, Zongwei Wang +3
With the rapid development of large language models, the generation of fake news has become increasingly effortless, posing a growing societal threat and underscoring the urgent ne…
When Does Divide and Conquer Work for Long Context LLM? A Noise Decomposition Framework
Zhen Xu, Shang Zhu, Jue Wang +5
We investigate the challenge of applying Large Language Models (LLMs) to long texts. We propose a theoretical framework that distinguishes the failure modes of long context tasks i…
BADGE: BADminton report Generation and Evaluation with LLM
Shang-Hsuan Chiang, Lin-Wei Chao, Kuang-Da Wang +2
Badminton enjoys widespread popularity, and reports on matches generally include details such as player names, game scores, and ball types, providing audiences with a comprehensive…
Assessing and Verifying Task Utility in LLM-Powered Applications
Negar Arabzadeh, Siqing Huo, Nikhil Mehta +5
The rapid development of Large Language Models (LLMs) has led to a surge in applications that facilitate collaboration among multiple agents, assisting humans in their daily tasks.…
StateFlow: Enhancing LLM Task-Solving through State-Driven Workflows
Yiran Wu, Tianwei Yue, Shaokun Zhang +2
It is a notable trend to use Large Language Models (LLMs) to tackle complex tasks, e.g., tasks that require a sequence of actions and dynamic interaction with tools and external en…