7 citations · 10 across the 4 of their papers we have counts for
6 papers
Agent Behavior as Code: Efficient and Robust LLM Agents with Programmatic Specifications
Peng Qi, Chunliang Lyu, Gang Li +4
AI agents based on foundation models (FMs) have demonstrated strong capabilities to perform complex open-ended tasks. However, they face some common challenges in practice: (a) age…
PADMÉ: Preference Alignment Data Synthesis for Meta-Evaluation of LM Agent Evaluators
Cheng Chang, Yining Mao, Peng Qi
Language models are frequently employed to evaluate other language models. An LM evaluator scoring agentic behaviors across multiple criteria is valuable, provided that its decisio…
WARC-Bench: Web Archive Based Benchmark for GUI Subtask Executions
Sanjari Srivastava, Gang Li, Cheng Chang +8
Training web agents to navigate complex, real-world websites requires them to master - short-horizon interactions on multiple UI components (e.g., choosing the…
Is Your LLM Secretly a World Model of the Internet? Model-Based Planning for Web Agents
Yu Gu, Kai Zhang, Yuting Ning +9
Language agents based on large language models (LLMs) have demonstrated great promise in automating web-based tasks. Recent work has shown that incorporating advanced planning algo…
Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents
Boyu Gou, Ruohan Wang, Boyuan Zheng +5
Multimodal large language models (MLLMs) are transforming the capabilities of graphical user interface (GUI) agents, facilitating their transition from controlled simulations to co…
Roleplay-doh: Enabling Domain-Experts to Create LLM-simulated Patients via Eliciting and Adhering to Principles
Ryan Louie, Ananjan Nandi, William Fang +3
Recent works leverage LLMs to roleplay realistic social scenarios, aiding novices in practicing their social skills. However, simulating sensitive interactions, such as in mental h…