You don't need a personality test to know these models are unreliable: Assessing the Reliability of Large Language Models on Psychometric Instruments.

[BibT_eX]

[DOI]

Bangzhao Shu

Lechen Zhang

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Understanding the Capabilities and Limitations of Large Language Models for Cultural Commonsense.

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Code Models are Zero-shot Precondition Reasoners.

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

When "A Helpful Assistant" Is Not Really Helpful: Personas in System Prompts Do Not Improve Performances of Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Prospector: Improving LLM Agents with Self-Asking and Trajectory Ranking.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Small Language Models Need Strong Verifiers to Self-Correct Reasoning.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

MultiPrompter: Cooperative Prompt Optimization with Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Exploring Demonstration Ensembling for In-context Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Discriminator-Guided Multi-step Reasoning with Language Models.

[BibT_eX]

[DOI]

CoRR, 2023

Multimodal Subtask Graph Generation from Instructional Videos.

[BibT_eX]

[DOI]

CoRR, 2023

Exploring the Benefits of Training Expert Language Models over Instruction Tuning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Merging Generated and Retrieved Knowledge for Open-Domain QA.

[BibT_eX]

[DOI]

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

TOD-Flow: Modeling the Structure of Task-Oriented Dialogues.

[BibT_eX]

[DOI]

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

A Picture is Worth a Thousand Words: Language Models Plan from Pixels.

[BibT_eX]

[DOI]

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

GRACE: Discriminator-Guided Chain-of-Thought Reasoning.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Unsupervised Task Graph Generation from Instructional Video Transcripts.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Few-shot Reranking for Multi-hop QA via Language Model Prompting.

[BibT_eX]

[DOI]

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Knowledge Unlearning for Mitigating Privacy Risks in Language Models.

[BibT_eX]

[DOI]

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Learning Compositional Tasks from Language Instructions.

[BibT_eX]

[DOI]

Lajanugen Logeswaran

Wilka Carvalho

Honglak Lee

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

LEPUS: Prompt-based Unsupervised Multi-hop Reranking for Open-domain QA.

[BibT_eX]

[DOI]

CoRR, 2022

Few-shot Subgoal Planning with Language Models.

[BibT_eX]

[DOI]

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

2021

Sample-efficient Learning and Generalization with Text Representations.

[BibT_eX]

[DOI]

Lajanugen Logeswaran

PhD thesis, 2021

2020

Few-shot Sequence Learning with Transformers.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Zero-Shot Entity Linking by Reading Entity Descriptions.

[BibT_eX]

[DOI]

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Content preserving text generation with attribute controls.

[BibT_eX]

[DOI]

Lajanugen Logeswaran

Honglak Lee

Samy Bengio

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

An efficient framework for learning sentence representations.

[BibT_eX]

[DOI]

Lajanugen Logeswaran

Honglak Lee

Proceedings of the 6th International Conference on Learning Representations, 2018

Sentence Ordering and Coherence Modeling using Recurrent Neural Networks.

[BibT_eX]

[DOI]

Lajanugen Logeswaran

Honglak Lee

Dragomir R. Radev

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2016

Sentence Ordering using Recurrent Neural Networks.

[BibT_eX]

[DOI]

Lajanugen Logeswaran

Honglak Lee

Dragomir R. Radev

CoRR, 2016

Generative Adversarial Text to Image Synthesis.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Performance, Resource, and Cost Aware Resource Provisioning in the Cloud.

[BibT_eX]

[DOI]

Lajanugen Logeswaran

H. M. N. Dilum Bandara

H. S. Bhathiya

Proceedings of the 9th IEEE International Conference on Cloud Computing, 2016

2014

Solving Jigsaw Puzzles using Paths and Cycles.

[BibT_eX]

[DOI]

Lajanugen Logeswaran

Proceedings of the British Machine Vision Conference, 2014

Lajanugen Logeswaran

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