Agents
Chain of Agents: Large Language Models Collaborating on Long-Context Tasks
Input reduction reduces the length of the input context before feeding to downstream LLMs.
Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models
The in-context learning (ICL) capability of pre-trained models based on the transformer architecture has received growing interest in recent years.
Sharpness-A ware Minimization Activates the Interactive Teaching's Understanding and Optimization
However, the underlying optimization principles and convergence of interactive teaching lack theoretical analysis, and in this regard co-teaching serves as a notable prototype.
MAC Advice for Facility Location Mechanism Design
We receive a prediction for each agent's location, and these predictions are crucially allowed to be only
Automating Data Annotation under Strategic Human Agents: Risks and Potential Solutions
A common practice to address this issue is using the model itself to annotate unlabeled data samples.
PUZZLES: A Benchmark for Neural Algorithmic Reasoning
These advancements have been enabled in part by the availability of benchmarks.
A Recipe for Building Adaptable Modular Knowledge Agents Through Process Feedback Jian Guan 1,2, Wei Wu
We focus on developing agents for knowledge-intensive tasks, where the agent completes users' information-seeking requests by interacting with specific knowledge bases [
