Philipp Sadler

According to our database1, Philipp Sadler authored at least 11 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
clembench-2024: A Challenging, Dynamic, Complementary, Multilingual Benchmark and Underlying Flexible Framework for LLMs as Multi-Action Agents.
CoRR, 2024

Learning Communication Policies for Different Follower Behaviors in a Collaborative Reference Game.
CoRR, 2024

The Unreasonable Ineffectiveness of Nucleus Sampling on Mitigating Text Memorization.
Proceedings of the 17th International Natural Language Generation Conference, 2024

Sharing the Cost of Success: A Game for Evaluating and Learning Collaborative Multi-Agent Instruction Giving and Following Policies.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

2023
clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Pento-DIARef: A Diagnostic Dataset for Learning the Incremental Algorithm for Referring Expression Generation from Examples.
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

Yes, this Way! Learning to Ground Referring Expressions into Actions with Intra-episodic Feedback from Supportive Teachers.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2020
Spatial Attention as an Interface for Image Captioning Models.
CoRR, 2020

From "Before" to "After": Generating Natural Language Instructions from Image Pairs in a Simple Visual Domain.
Proceedings of the 13th International Conference on Natural Language Generation, 2020

2019
Can Neural Image Captioning be Controlled via Forced Attention?
Proceedings of the 12th International Conference on Natural Language Generation, 2019

2018
Detecting cities in aerial night-time images by learning structural invariants using single reference augmentation.
CoRR, 2018


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