inside sika-agent

Inside Sika Agent

Right, per task and language

Share of matched episodes the agent got right; ▲ = episodes that harmed the user. Same seeds, wallets and expected outcomes in every column. Flips: twins right in English but not here / right here but not in English.

Read-outs

Language of the model's reasoning

Share of reasoning words tagged English, Twi or mixed, by request language.

Receiver-head attention per sentence

Mean vertical score of the top-20 receiver heads, per sentence, by source and request language (first turns). Right: Twi–English and Twi minus the English twin, 95% bootstrap interval over twins.

Scam probe trained on English requests

Accuracy reading held-out seeds at the end of the request, by layer. Dashed: bag of words on the request text.

Task-type probe trained on English requests

20 classes; chance 5%. Dashed: bag of words.

Twi–English nearer its English twin

Share of Twi–English requests whose state is nearer the English twin's than the Twi twin's (centred cosine), by layer.

Placement of failed vs right Twi–English episodes

Mean placement margin (cos to English twin − cos to Twi twin, centred within task type) of failed minus right episodes. Below 0: failures sit nearer the Twi twin. ● p < 0.001 (within-type permutation).

Scam signal under masking, Twi–English requests

English-trained scam probe at the end of the request, as written and with words masked (…), by layer.

Words of Twi–English requests read as Twi

Token probe trained on English vs Twi requests; mean over a word's tokens, by layer. Mixed: English stem in Twi grammar (a-send-i).

State change between tokens

1 − cosine between consecutive tokens' residual states in Twi–English requests: at a language switch vs elsewhere.

Probes after reasoning, within each language

Best layer at the last reasoning token. Scam base rate 65%.

Steering at every decision

Each cell: one neuron's write direction added at the positions where the model chooses its move (± dose × residual norm), at one decision. Colour: shift of the margin toward the right move (lime) or the wrong/harmful one (coral), in nats; or its percentile among 32 random directions at the same layer, decision, sign and dose. Select a cell, a circuit node or a point on the map; the inspector follows.

Steered replays

Episodes replayed from a decision with one direction added after its layer at every token for the rest of the episode (dose × residual norm), against the same simulator and scripted user; graded like the original episodes. Unsteered: the same replays with nothing added.

Thought anchors

Filled ring: model turn, size = change in mean outcome replaying from it vs from the next turn (10 replays per turn); colour = what it did. Hollow ring: input, size = largest KL its removal causes in a later turn. Arcs: step → later turn, width = mean KL over that turn's tokens. Select a step; the inspector shows its text shaded by receiver-head score.