Replays
An agent's research run, played back: what it searched, which pages it read, and how each citation in its answer checked out.
Another important tool is mechanistic analysis, i.e. studying the model's weights and activations for understanding how it functions, which has been shown to fully explain the behavior of entire neural networks (Nanda et al., 2023; Olah et al., 2020).
5 verified1 page only0 rejected
Using individual neurons as these units has had some success (Olah et al., 2020; Bills et al., 2023), but a key challenge has been that neurons are often polysemantic, activating for several unrelated types of feature (Olah et al., 2020).4 verified2 page only6 rejected
Another important tool is mechanistic analysis, i.e. studying the model’s weights and activations for understanding how it functions (Nanda et al., 2023; Olah et al., 2020).8 verified0 page only1 rejected
Using individual neurons as these units has had some success (Olah et al., 2020; Bills et al., 2023), but a key challenge has been that neurons are almost always polysemantic, with nearly every neuron activating for several unrelated types of feature (Olah et al., 2020).3 verified0 page only1 rejected
Another important tool is mechanistic analysis, i.e. studying the model's weights and activations for understanding how it functions, which has been shown to fully explain the behavior of entire neural networks (Nanda et al., 2023; Olah et al., 2020).3 verified2 page only1 rejected
Using individual neurons as these units has had some success (Olah et al., 2020; Bills et al., 2023), but a key challenge has been that neurons are often polysemantic, activating for several unrelated types of feature (Olah et al., 2020).4 verified0 page only2 rejected
Another important tool is mechanistic analysis, i.e. studying the model’s weights and activations for understanding how it functions (Nanda et al., 2023; Olah et al., 2020).4 verified0 page only2 rejected
Using individual neurons as these units has had some success (Olah et al., 2020; Bills et al., 2023), but a key challenge has been that neurons are almost always polysemantic, with nearly every neuron activating for several unrelated types of feature (Olah et al., 2020).3 verified0 page only1 rejected
Another important tool is mechanistic analysis, i.e. studying the model's weights and activations for understanding how it functions, which has been shown to fully explain the behavior of entire neural networks (Nanda et al., 2023; Olah et al., 2020).0 verified0 page only3 rejected
Using individual neurons as these units has had some success (Olah et al., 2020; Bills et al., 2023), but a key challenge has been that neurons are often polysemantic, activating for several unrelated types of feature (Olah et al., 2020).3 verified1 page only1 rejected
Another important tool is mechanistic analysis, i.e. studying the model’s weights and activations for understanding how it functions (Nanda et al., 2023; Olah et al., 2020).1 verified1 page only5 rejected
Using individual neurons as these units has had some success (Olah et al., 2020; Bills et al., 2023), but a key challenge has been that neurons are almost always polysemantic, with nearly every neuron activating for several unrelated types of feature (Olah et al., 2020).1 verified5 page only1 rejected
Another important tool is mechanistic analysis, i.e. studying the model's weights and activations for understanding how it functions, which has been shown to fully explain the behavior of entire neural networks (Nanda et al., 2023; Olah et al., 2020).2 verified0 page only0 rejected
Using individual neurons as these units has had some success (Olah et al., 2020; Bills et al., 2023), but a key challenge has been that neurons are often polysemantic, activating for several unrelated types of feature (Olah et al., 2020).0 verified1 page only1 rejected
Another important tool is mechanistic analysis, i.e. studying the model’s weights and activations for understanding how it functions (Nanda et al., 2023; Olah et al., 2020).0 verified2 page only3 rejected
Using individual neurons as these units has had some success (Olah et al., 2020; Bills et al., 2023), but a key challenge has been that neurons are almost always polysemantic, with nearly every neuron activating for several unrelated types of feature (Olah et al., 2020).0 verified2 page only2 rejected
Another important tool is mechanistic analysis, i.e. studying the model's weights and activations for understanding how it functions, which has been shown to fully explain the behavior of entire neural networks (Nanda et al., 2023; Olah et al., 2020).0 verified1 page only3 rejected
Using individual neurons as these units has had some success (Olah et al., 2020; Bills et al., 2023), but a key challenge has been that neurons are often polysemantic, activating for several unrelated types of feature (Olah et al., 2020).0 verified6 page only0 rejected
Another important tool is mechanistic analysis, i.e. studying the model’s weights and activations for understanding how it functions (Nanda et al., 2023; Olah et al., 2020).0 verified5 page only0 rejected
Using individual neurons as these units has had some success (Olah et al., 2020; Bills et al., 2023), but a key challenge has been that neurons are almost always polysemantic, with nearly every neuron activating for several unrelated types of feature (Olah et al., 2020).2 verified0 page only1 rejected
Another important tool is mechanistic analysis, i.e. studying the model's weights and activations for understanding how it functions, which has been shown to fully explain the behavior of entire neural networks (Nanda et al., 2023; Olah et al., 2020).2 verified0 page only1 rejected
Using individual neurons as these units has had some success (Olah et al., 2020; Bills et al., 2023), but a key challenge has been that neurons are often polysemantic, activating for several unrelated types of feature (Olah et al., 2020).3 verified0 page only1 rejected
Another important tool is mechanistic analysis, i.e. studying the model’s weights and activations for understanding how it functions (Nanda et al., 2023; Olah et al., 2020).2 verified0 page only1 rejected
Using individual neurons as these units has had some success (Olah et al., 2020; Bills et al., 2023), but a key challenge has been that neurons are almost always polysemantic, with nearly every neuron activating for several unrelated types of feature (Olah et al., 2020).2 verified1 page only1 rejected