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Found 6 papers, 5 papers with code
Benchmarking Failures in Tool-Augmented Language Models
Further, to study possible mitigation of the failures, we enable real-time human interaction, named the Ask-and-Help (AAH) method, to provide missing information or replace non-functional tools.
CowPilot: A Framework for Autonomous and Human-Agent Collaborative Web Navigation
CowPilot reduces the number of steps humans need to perform by allowing agents to propose next steps, while users are able to pause, reject, or take alternative actions.
AutoPresent: Designing Structured Visuals from Scratch
We benchmark end-to-end image generation and program generation methods with a variety of models, and find that programmatic methods produce higher-quality slides in user-interactable formats.
Agent Workflow Memory
Despite the potential of language model-based agents to solve real-world tasks such as web navigation, current methods still struggle with long-horizon tasks with complex action trajectories.
ECCO: Can We Improve Model-Generated Code Efficiency Without Sacrificing Functional Correctness?
Although large language models (LLMs) have been largely successful in generating functionally correct programs, conditioning models to produce efficient solutions while ensuring correctness remains a challenge.
CodeRAG-Bench: Can Retrieval Augment Code Generation?
We aggregate documents from five sources for models to retrieve contexts: competition solutions, online tutorials, library documentation, StackOverflow posts, and GitHub repositories.
