Shelby Heinecke

Orcid: 0000-0002-8831-0753

According to our database1, Shelby Heinecke authored at least 31 papers between 2018 and 2024.

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Bibliography

2024
PRACT: Optimizing Principled Reasoning and Acting of LLM Agent.
CoRR, 2024

xLAM: A Family of Large Action Models to Empower AI Agent Systems.
CoRR, 2024

xGen-MM (BLIP-3): A Family of Open Large Multimodal Models.
CoRR, 2024

Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents.
CoRR, 2024

Personalized Multi-task Training for Recommender System.
CoRR, 2024

APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets.
CoRR, 2024

MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases.
CoRR, 2024

AgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System.
CoRR, 2024

AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning.
CoRR, 2024

Editing Arbitrary Propositions in LLMs without Subject Labels.
CoRR, 2024

Towards More Robust and Accurate Sequential Recommendation with Cascade-guided Adversarial Training.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

Causal Layering via Conditional Entropy.
Proceedings of the Causal Learning and Reasoning, 2024

2023
Deconfounded Causal Collaborative Filtering.
Trans. Recomm. Syst., December, 2023

DRDT: Dynamic Reflection with Divergent Thinking for LLM-based Sequential Recommendation.
CoRR, 2023

BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents.
CoRR, 2023

Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization.
CoRR, 2023

REX: Rapid Exploration and eXploitation for AI Agents.
CoRR, 2023

On the Unlikelihood of D-Separation.
CoRR, 2023

Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data.
CoRR, 2023

Enhancing Performance on Seen and Unseen Dialogue Scenarios using Retrieval-Augmented End-to-End Task-Oriented System.
Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue, 2023

Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Tackling Data Heterogeneity in Federated Learning with Class Prototypes.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Dynamic Causal Collaborative Filtering.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
Combining Data-driven Supervision with Human-in-the-loop Feedback for Entity Resolution.
CoRR, 2021

Deconfounded Causal Collaborative Filtering.
CoRR, 2021

Communication-Aware Collaborative Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019
Crowdsourced PAC Learning under Classification Noise.
Proceedings of the Seventh AAAI Conference on Human Computation and Crowdsourcing, 2019

2018
On the Resilience of Bipartite Networks.
Proceedings of the 56th Annual Allerton Conference on Communication, 2018


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