Interpretability · Activation Steering

Empathy Is Steerable
but Multi-Axial

JuHeon Ha · Byounghan Lee · Yunseo Choi · Kyung-Ah Sohn

Department of Artificial Intelligence, Ajou University

EMNLP 2026 · Main Conference

Supportive empathy is evaluated along several dimensions at once. We asked whether those evaluation dimensions correspond to directions a model can actually be steered along — independently.

Activation steering can control traits like honesty, refusal, and sycophancy by adding a direction to a model's residual stream. Empathy is harder: a response can acknowledge feeling, interpret a situation, or invite elaboration, and a single aggregate score hides which of these actually moved.

Using the EPITOME framework, which scores peer-support replies on Emotional Reactions, Interpretations, and Explorations, we extracted one candidate direction per dimension in three instruction-tuned LLMs and intervened on each — measuring both its target effect and what it did to the other two.

What we found

Steerable, but not separately

9/9target effects

A shared operating point exists

At layer 15 and α = +1, every model–dimension pair moved its target score in the intended direction across Llama-3.1-8B, Qwen2.5-7B, and Mistral-7B. Later layers were model-dependent; the final layer was unstable.

−0.22ER under EX steering

Steering one dimension moves the others

Pushing EX up on Llama raised it by +0.57 — and pulled ER down by 0.22. The directions are causally effective but not isolated controls.

~3%of persona shift captured

Persona effects live somewhere else

Persona prompts change EPITOME scores substantially, yet the recovered ER/IP/EX span accounts for only 2.6–3.1% of the squared activation shift they induce. The remaining ~97% is structured, but outside this basis.

Method

One direction per dimension

For each mechanism we built contrastive pools from human-annotated EPITOME labels — 100 replies scoring 1 or 2 against 100 scoring 0 — and took the mean difference of last-token residual-stream activations. Adding α·v at inference gives a steering knob; scoring the generations with the EPITOME classifiers gives the effect.

The design point that matters: we score all three dimensions after steering any one of them. Target effects alone would look like clean control.

Pipeline: contrastive EPITOME pools feed vector extraction at layer 15, then steered generation is scored on all three mechanisms.
Extraction and intervention. Contrastive pools built from EPITOME labels yield one candidate direction per mechanism at the canonical layer, applied during generation and scored back on all three dimensions.

Behavior

What steering actually changes

One seeker post with three steered responses: ER adds emotional acknowledgment, IP adds an interpretation, EX adds a follow-up question.
The same post, three directions. ER steering adds emotional acknowledgment, IP steering adds an interpretation of the seeker's situation, and EX steering adds a follow-up question inviting elaboration.

Across the layer sweep, the middle of the network is where this control is both effective and consistent between models — a result that matches prior contrastive-activation findings.

Layer sweep showing mechanism-targeted steering effects across candidate layers for three models.
Layer sweep. Target effects across candidate layers and steering strengths. Layer 15 is the most consistent shared operating point; at the final valid layer, ER collapses from 1.03 to 0.005 on Mistral while IP rises sharply — behavior that varies by model and mechanism.

Geometry

The directions overlap

If the three dimensions were independent axes, their vectors would be near-orthogonal. They are not. IP sits at a consistently negative angle to both of the others in all three models — the geometric counterpart of the behavioral spillovers.

ER EX IP

Pairwise cosine at layer 15

  • ER · EX+0.078
  • ER · IP−0.293
  • EX · IP−0.448

Llama-3.1-8B. The same sign pattern holds on Qwen2.5-7B (+0.126, −0.322, −0.463) and Mistral-7B (+0.091, −0.248, −0.533). Residualizing each vector against the other two weakens EX and IP control, so the shared component carries function — not just norm.

Cross-mechanism deltas · Llama-3.1-8B · layer 15 · α = +1

SteeringΔERΔIPΔEX
ER vector+0.08−0.15+0.01
IP vector−0.06+0.32+0.02
EX vector−0.22−0.06+0.57

Diagonal cells are target effects; off-diagonal cells are spillovers, measured against the matching α = 0 baseline. Every vector moves its own dimension — and at least one other.

Persona

Where persona effects go

Persona prompts (“You are an engineer.”, “You are a cynical person.”) shift EPITOME scores by as much as 0.74 on ER. If those shifts moved along the recovered directions, a single steering vector could close persona-conditioned gaps.

They don't. Projecting each persona-mean activation shift onto the orthonormalized ER/IP/EX span captures only 2.6–3.1% of its squared magnitude. The residual is not noise — its top five principal components explain 27–30% of residual variance — but it lies outside the basis these vectors recover.

Decomposition showing the mechanism subspace captures a small fraction of persona-induced activation shift, with structured residual variation.
Persona-shift decomposition. Left: fraction of persona-mean squared activation shift captured by the ER/IP/EX subspace. Right: persona centroids in the first two residual principal components, after removing the mechanism-subspace component.

Dimensions used to evaluate supportive empathy need not provide independent intervention targets.

Control analysis

Is the coupling an artifact?

A natural worry: extraction pools drawn on one label are imbalanced on the others, so a “direction for ER” might partly encode the absence of IP and EX. We tested it. On Llama at layer 15, we re-extracted vectors from pools exactly matched on the 0/1/2 levels of both non-target labels, and compared them against unmatched pools drawn from the same candidate set — holding target-label counts, the 200 evaluation seekers, and decoding fixed.

VectorMatched Δtarget95% CI
ER+0.065[0.005, 0.125]
EX+0.610[0.460, 0.760]
IP+0.270[0.130, 0.410]

Target effects survive exact matching, and none of the differences between arms is significant. Matching does attenuate one spillover — ER suppression under EX steering, from −0.12 to −0.05 — so pool composition contributes to some coupling without being necessary for steerability. This is a one-seed, Llama-only check; it does not establish that the pattern is specific to empathy.

Scope

What this does and doesn't show

All claims are restricted to supportive empathy as operationalized by EPITOME in online peer support. EPITOME defines a specific, domain-bound construct; what counts as empathic elsewhere may differ, and we make no claim about empathy in general.

Evaluation is proxy-based throughout — EPITOME classifiers and a GPT-5-mini judge, which agree on the ER and EX directional patterns but less on IP. We collected no human annotations, so these results describe proxy-scored expression, not perceived empathic support. The persona set is narrow and US-centric, used as controlled probes rather than a representative demographic sample. Whether partial separability is specific to empathy remains open; that would need a matched non-empathy multidimensional control.