REVIEW 10 cited by
The Dawn of GUI Agent: A Preliminary Case Study with Claude 3.5 Computer Use
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
The recently released model, Claude 3.5 Computer Use, stands out as the first frontier AI model to offer computer use in public beta as a graphical user interface (GUI) agent. As an early beta, its capability in the real-world complex environment remains unknown. In this case study to explore Claude 3.5 Computer Use, we curate and organize a collection of carefully designed tasks spanning a variety of domains and software. Observations from these cases demonstrate Claude 3.5 Computer Use's unprecedented ability in end-to-end language to desktop actions. Along with this study, we provide an out-of-the-box agent framework for deploying API-based GUI automation models with easy implementation. Our case studies aim to showcase a groundwork of capabilities and limitations of Claude 3.5 Computer Use with detailed analyses and bring to the fore questions about planning, action, and critic, which must be considered for future improvement. We hope this preliminary exploration will inspire future research into the GUI agent community. All the test cases in the paper can be tried through the project: https://github.com/showlab/computer_use_ootb.
Forward citations
Cited by 10 Pith papers
-
GUI-AIMA: Aligning Intrinsic Multimodal Attention with a Context Anchor for GUI Grounding
Supervising an MLLM's intrinsic self-attention with patch-level GUI labels, aggregated via a learnable anchor token and hidden-state-selected query tokens, reaches state-of-the-art 3B-scale GUI grounding accuracy with...
-
MobilityBench: A Benchmark for Evaluating Route-Planning Agents in Real-World Mobility Scenarios
MobilityBench is a 100,000-episode benchmark with a replay sandbox for deterministic evaluation of LLM route-planning agents; current models score well on basic tasks but fail preference-constrained routing.
-
Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight
GUI agents frequently fall for deceptive interface designs, often without recognizing them, and human supervision of agents improves avoidance only partially while introducing new attention and workload costs.
-
AgentSentinel: An End-to-End and Real-Time Security Defense Framework for Computer-Use Agents
AgentSentinel combines system-level tracing with LLM-based auditing to block 79.6% of attacks in the authors' 60-scenario computer-use agent benchmark.
-
What Limits Virtual Agent Application? OmniBench: A Scalable Multi-Dimensional Benchmark for Essential Virtual Agent Capabilities
A self-generating graph benchmark produces 36k GUI agent tasks with controllable complexity and ten capability scores, and fine-tuning on its trajectories gives small gains on AndroidControl and OmniAct.
-
GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents
An attention-based action head with multi-patch supervision outperforms coordinate-generation baselines on GUI grounding, and a verifier further improves accuracy.
-
Plover: Steering GUI Agents through Plan-Centric Interaction
An expert repairing visible plans rescued 23 of 26 failed GUI automation runs, turning 17 into full and 6 into partial successes.
-
OmniActor: A Generalist GUI and Embodied Agent for 2D&3D Worlds
A generalist agent with shared shallow layers and task-separated deep experts outperforms single-domain GUI and embodied agents on AndroidControl, GUI-Odyssey, and LIBERO benchmarks.
-
Mirage-1: Augmenting and Updating GUI Agent with Hierarchical Multimodal Skills
Mirage-1 combines a hierarchical multimodal skill memory with a skill-augmented Monte Carlo tree search to outperform prior GUI agents on Android and web online benchmarks.
-
How Small Transformation Expose the Weakness of Semantic Similarity Measures
A diagnostic benchmark of text and code transformations finds embedding similarity metrics often conflate opposition with equivalence; LLM judges discriminate better, and Euclidean distance improves code embeddings.
Discussion (0). Sign in to comment.