Reference Summary: State-of-the-art foundation models are often seen as black boxes: we send a prompt in and we get out our - often useful - answer. This video summarizes the research by Eric Bigelow, Daniel Wurgaft, and colleagues from Goodfire AI, Harvard, NTT Research, ...

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State-of-the-art foundation models are often seen as black boxes: we send a prompt in and we get out our - often useful - answer. This video summarizes the research by Eric Bigelow, Daniel Wurgaft, and colleagues from Goodfire AI, Harvard, NTT Research, ... In this AI Research Roundup episode, Alex discusses the paper: 'ASA: Training-Free Representation Engineering for Tool-Calling ...

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  • State-of-the-art foundation models are often seen as black boxes: we send a prompt in and we get out our - often useful - answer.
  • This video summarizes the research by Eric Bigelow, Daniel Wurgaft, and colleagues from Goodfire AI, Harvard, NTT Research, ...
  • In this AI Research Roundup episode, Alex discusses the paper: 'ASA: Training-Free Representation Engineering for Tool-Calling ...

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Steering LLM Behavior Without Fine-Tuning

Steering LLM Behavior Without Fine-Tuning

Read more details and related context about Steering LLM Behavior Without Fine-Tuning.

Steering LLMs: How to Change AI Personality Without Fine-Tuning

Steering LLMs: How to Change AI Personality Without Fine-Tuning

Read more details and related context about Steering LLMs: How to Change AI Personality Without Fine-Tuning.

Steering LLM Behavior Without Fine-Tuning | Practical Control Techniques

Steering LLM Behavior Without Fine-Tuning | Practical Control Techniques

Read more details and related context about Steering LLM Behavior Without Fine-Tuning | Practical Control Techniques.

How Belief Dynamics Control LLMs: ICL and Activation Steering Unified

How Belief Dynamics Control LLMs: ICL and Activation Steering Unified

This video summarizes the research by Eric Bigelow, Daniel Wurgaft, and colleagues from Goodfire AI, Harvard, NTT Research, ...

LLM Interpretability - How to steer its features?

LLM Interpretability - How to steer its features?

Read more details and related context about LLM Interpretability - How to steer its features?.

ASA: Training-Free Steering for LLM Tool-Calling

ASA: Training-Free Steering for LLM Tool-Calling

In this AI Research Roundup episode, Alex discusses the paper: 'ASA: Training-Free Representation Engineering for Tool-Calling ...

How to Master an LLM Without Training (A Technique Few Know)

How to Master an LLM Without Training (A Technique Few Know)

Join my AI Academy: Want to develop advanced AI solutions? IG: https ...

Steering vectors: tailor LLMs without training. Part I: Theory (Interpretability Series)

Steering vectors: tailor LLMs without training. Part I: Theory (Interpretability Series)

State-of-the-art foundation models are often seen as black boxes: we send a prompt in and we get out our - often useful - answer.

How LLM Behavior Can Be Changed Without Retraining

How LLM Behavior Can Be Changed Without Retraining

Read more details and related context about How LLM Behavior Can Be Changed Without Retraining.

🧠🤯 Steer LLMs WITHOUT Fine-Tuning?! #easy2digital #LLMSteering

🧠🤯 Steer LLMs WITHOUT Fine-Tuning?! #easy2digital #LLMSteering

Read more details and related context about 🧠🤯 Steer LLMs WITHOUT Fine-Tuning?! #easy2digital #LLMSteering.