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2020 – today
- 2024
[i7]Will LeVine, Benjamin Pikus, Jacob Phillips, Berk Norman, Fernando Amat Gil, Sean Hendryx:
Out-of-Distribution Detection & Applications With Ablated Learned Temperature Energy. CoRR abs/2401.12129 (2024)- [i6]Hugh Zhang, Jeff Da, Dean Lee, Vaughn Robinson, Catherine Wu, Will Song, Tiffany Zhao, Pranav Raja, Dylan Slack, Qin Lyu, Sean Hendryx, Russell Kaplan, Michele Lunati, Summer Yue:
A Careful Examination of Large Language Model Performance on Grade School Arithmetic. CoRR abs/2405.00332 (2024) - [i5]Vaskar Nath, Dylan Slack, Jeff Da, Yuntao Ma, Hugh Zhang, Spencer Whitehead, Sean Hendryx:
Learning Goal-Conditioned Representations for Language Reward Models. CoRR abs/2407.13887 (2024) - [i4]Spencer Whitehead, Jacob Phillips, Sean Hendryx:
Pre-Training Multimodal Hallucination Detectors with Corrupted Grounding Data. CoRR abs/2409.00238 (2024) - [i3]Evan Wang, Federico Cassano, Catherine Wu, Yunfeng Bai, Will Song, Vaskar Nath, Ziwen Han, Sean Hendryx, Summer Yue, Hugh Zhang:
Planning In Natural Language Improves LLM Search For Code Generation. CoRR abs/2409.03733 (2024) - [i2]Mohit Raghavendra, Vaskar Nath, Sean Hendryx:
Revisiting the Superficial Alignment Hypothesis. CoRR abs/2410.03717 (2024) - 2023
- [i1]Benjamin Pikus, Will LeVine, Tony Chen, Sean Hendryx:
A Baseline Analysis of Reward Models' Ability To Accurately Analyze Foundation Models Under Distribution Shift. CoRR abs/2311.14743 (2023)
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