1 citations · 1 across the 11 of their papers we have counts for
13 papers
Terrarium: Growing Personal Assistants via Scalable Synthesis of App Worlds
Mengzhou Wu, Yuzhe Guo, Jiawen Tao +9
Advances in large language models (LLMs) have brought the vision of a general-purpose personal assistant closer to reality. Such assistants could provide a unified natural-language…
Beyond Accuracy: Prefix-Invariant Realizations of Low-Precision Fast Matrix Multiplication
Shuxiao Xie, Shuyang Xie, Yuan Cao +3
Fast matrix multiplication saves multiplications through exact cancellation, but rounding sums that mix token rows can leave contributions from later tokens in earlier language mod…
Fast Matrix Multiplication in fp8: Certified Coefficient Optimization and Measured Error
Shuxiao Xie, Shuyang Xie, Yuan Cao +3
A Strassen-type algorithm has many realizations with the same exact product and multiplication count yet different fp8 error because basis changes reshape coefficient geometry, pos…
One QK Channel, Many Sources: Tracing Low-Precision Attention Collapse
Shuxiao Xie, Shuyang Xie, Yuan Cao +3
A bfloat16 transformer can train normally, then collapse abruptly. Prior work links collapse to structured attention errors and shows QK normalization disrupts their compounding. D…
BackendForge: Benchmarking Agentic End-to-End Code Generation with Backend Services
Yuzhe Guo, Mengzhou Wu, Yuan Cao +4
Large language models (LLMs) are increasingly used in agentic coding settings, where they can inspect files, execute commands, run tests, observe failures, and iteratively revise c…
Bridging the Last Mile of Circuit Design: PostEDA-Bench, a Hierarchical Benchmark for PPA Convergence and DRC Fixing
Pengju Liu, Nuo Xu, Jinwei Tang +2
LLM-based agents are increasingly applied to the "last mile" of Electronic Design Automation (EDA): repairing residual sign-off Design Rule Check (DRC) violations and converging Po…
UI-Oceanus: Scaling GUI Agents with Synthetic Environmental Dynamics
Mengzhou Wu, Yuzhe Guo, Yuan Cao +16
Scaling generalist GUI agents is hindered by the data scalability bottleneck of expensive human demonstrations and the "distillation ceiling" of synthetic teacher supervision. To t…
An Empirical Study and Theoretical Explanation on Task-Level Model-Merging Collapse
Yuan Cao, Dezhi Ran, Yuzhe Guo +5
Model merging unifies independently fine-tuned LLMs from the same base, enabling reuse and integration of parallel development efforts without retraining. However, in practice we o…
From User Interface to Agent Interface: Efficiency Optimization of UI Representations for LLM Agents
Dezhi Ran, Zhi Gong, Yuzhe Guo +10
While Large Language Model (LLM) agents show great potential for automated UI navigation such as automated UI testing and AI assistants, their efficiency has been largely overlooke…
AppForge: From Assistant to Independent Developer -- Are GPTs Ready for Software Development?
Dezhi Ran, Yuan Cao, Mengzhou Wu +10
Large language models (LLMs) have demonstrated remarkable capability in function-level code generation tasks. Unlike isolated functions, real-world applications demand reasoning ov…
Beyond Pass or Fail: Multi-Dimensional Benchmarking of Foundation Models for Goal-based Mobile UI Navigation
Dezhi Ran, Mengzhou Wu, Hao Yu +15
Recent advances of foundation models (FMs) have made navigating mobile applications (apps) based on high-level goal instructions within reach, with significant industrial applicati…
An Infrastructure Software Perspective Toward Computation Offloading between Executable Specifications and Foundation Models
Dezhi Ran, Mengzhou Wu, Yuan Cao +3
Foundation Models (FMs) have become essential components in modern software systems, excelling in tasks such as pattern recognition and unstructured data processing. However, their…
Skill-Adaptive Imitation Learning for UI Test Reuse
Mengzhou Wu, Hao Wang, Jun Ren +7
To alleviate the substantial cost of manually crafting user interface (UI) test cases, UI test migration aims to automatically generate test cases for a target mobile application (…