
Sign up to save your podcasts
Or


In an era dominated by direct preference optimization and LLMasajudge, why do we still need a model to output only a scalar reward?
This is AI generated audio with Python and 11Labs. Music generated by Meta's MusicGen.
Source code: https://github.com/natolambert/interconnects-tools
Original post: In an era dominated by direct preference optimization and LLM-as-a-judge, why do we still need a model to output only a scalar reward?
Podcast figures:
Figure 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reward-models/img_004.png
Figure 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reward-models/img_009.png
0:00 Why reward models are still key to understanding alignment
By Nathan Lambert4.1
99 ratings
In an era dominated by direct preference optimization and LLMasajudge, why do we still need a model to output only a scalar reward?
This is AI generated audio with Python and 11Labs. Music generated by Meta's MusicGen.
Source code: https://github.com/natolambert/interconnects-tools
Original post: In an era dominated by direct preference optimization and LLM-as-a-judge, why do we still need a model to output only a scalar reward?
Podcast figures:
Figure 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reward-models/img_004.png
Figure 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reward-models/img_009.png
0:00 Why reward models are still key to understanding alignment

538 Listeners

1,087 Listeners

289 Listeners

211 Listeners

200 Listeners

305 Listeners

95 Listeners

501 Listeners

131 Listeners

93 Listeners

227 Listeners

152 Listeners

467 Listeners

35 Listeners

39 Listeners