content.raw: 🔍 Today's pick in Interpretability & Analysis of LMs: x2 edition!
content.type: text
content.value: 🔍 Today's pick in Interpretability & Analysis of LMs: x2 edition!
content.type: new_line
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content.raw: Today's highlighted works aim reproduce findings from Transformer-centric interpretability literature on new RNN-based architectures such as Mamba and RWKV:
content.type: text
content.value: Today's highlighted works aim reproduce findings from Transformer-centric interpretability literature on new RNN-based architectures such as Mamba and RWKV:
content.type: new_line
content.type: new_line
content.label: Does Transformer Interpretability Transfer to RNNs? (2404.05971)
content.raw: https://huggingface.co/papers/2404.05971
content.id: 2404.05971
content.type: paper
content.type: resource
content.url: https://huggingface.co/papers/2404.05971
content.raw:  by 
content.type: text
content.value:  by 
content.raw: @MrGonao
content.type: mention
content.user: MrGonao
content.raw:  T. Marshall 
content.type: text
content.value:  T. Marshall 
content.raw: @norabelrose
content.type: mention
content.user: norabelrose
content.type: new_line
content.type: new_line
content.label: Locating and Editing Factual Associations in Mamba (2404.03646)
content.raw: https://huggingface.co/papers/2404.03646
content.id: 2404.03646
content.type: paper
content.type: resource
content.url: https://huggingface.co/papers/2404.03646
content.raw:   by 
content.type: text
content.value:   by 
content.raw: @sensharma
content.type: mention
content.user: sensharma
content.type: text
content.raw: @datkinson
content.type: mention
content.user: datkinson
content.type: text
content.raw: @davidbau
content.type: mention
content.user: davidbau
content.type: new_line
content.type: new_line
content.raw: The first paper applies contrastive activation addition, the tuned lens and probing for eliciting latent knowledge in quirky models to Mamba and RWKV LMs, finding these Transformer-specific methods can be applied with slight adaptation to these architectures, obtaining similar results.
content.type: text
content.value: The first paper applies contrastive activation addition, the tuned lens and probing for eliciting latent knowledge in quirky models to Mamba and RWKV LMs, finding these Transformer-specific methods can be applied with slight adaptation to these architectures, obtaining similar results.
content.type: new_line
content.type: new_line
content.raw: The second work applies the ROME method to Mamba, finding weights playing the role of MLPs in encoding factual relations across several Mamba layers, and can be patched to perform model editing. A new SSM-specific technique is also introduced to emulate attention knockout (value zeroing) revealing information flows similar to the ones in Transformers when processing factual statements.
content.type: text
content.value: The second work applies the ROME method to Mamba, finding weights playing the role of MLPs in encoding factual relations across several Mamba layers, and can be patched to perform model editing. A new SSM-specific technique is also introduced to emulate attention knockout (value zeroing) revealing information flows similar to the ones in Transformers when processing factual statements.
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content.raw: 💻 Code: 
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content.value: 💻 Code: 
content.href: https://github.com/arnab-api/romba
content.raw: https://github.com/arnab-api/romba
content.type: link
content.type: new_line
content.type: new_line
content.raw: 🔍 All daily picks: 
content.type: text
content.value: 🔍 All daily picks: 
content.href: https://huggingface.co/collections/gsarti/daily-picks-in-interpretability-and-analysis-ofc-lms-65ae3339949c5675d25de2f9
content.raw: https://huggingface.co/collections/gsarti/daily-picks-in-interpretability-and-analysis-ofc-lms-65ae3339949c5675d25de2f9
content.type: link
rawContent: 🔍 Today's pick in Interpretability & Analysis of LMs: x2 edition!
  
  Today's highlighted works aim reproduce findings from Transformer-centric interpretability literature on new RNN-based architectures such as Mamba and RWKV:
  
  https://huggingface.co/papers/2404.05971 by @MrGonao T. Marshall @norabelrose
  
  https://huggingface.co/papers/2404.03646  by @sensharma @datkinson @davidbau
  
  The first paper applies contrastive activation addition, the tuned lens and probing for eliciting latent knowledge in quirky models to Mamba and RWKV LMs, finding these Transformer-specific methods can be applied with slight adaptation to these architectures, obtaining similar results.
  
  The second work applies the ROME method to Mamba, finding weights playing the role of MLPs in encoding factual relations across several Mamba layers, and can be patched to perform model editing. A new SSM-specific technique is also introduced to emulate attention knockout (value zeroing) revealing information flows similar to the ones in Transformers when processing factual statements.
  
  💻 Code: https://github.com/arnab-api/romba
  
  🔍 All daily picks: https://huggingface.co/collections/gsarti/daily-picks-in-interpretability-and-analysis-ofc-lms-65ae3339949c5675d25de2f9
reactions.reaction: ❤️
reactions.users: samusenps osanseviero clem datkinson
reactions.reaction: 🔥
reactions.users: samusenps osanseviero clem datkinson