Kovač and coauthors study a narrower question than whether an LLM “has values”: whether the ordering of the values it expresses is preserved when an apparently unrelated conversational context changes. They administer the 40-item Portrait Values Questionnaire (PVQ-40) to 21 models from six families after conversations about grammar, jokes, poetry, history, or chess. In one condition, each model role-plays 60 Tolkien characters or 50 famous people; in another, it receives no persona. The tested model converses with a second instance of the same model, and each questionnaire response is the highest-scoring A–F next-token option. Scores are centered within participant and aggregated into Schwartz's ten values.
Rank-order stability asks whether differences among simulated people retain the same ordering across two topics: for example, whether personas expressing more Tradition in one context remain relatively high in another. Ipsative stability asks whether the ordering of the ten values within one participant is preserved across contexts. These are different properties. A model may retain a similar within-profile ordering while failing to preserve differences among personas; it may also obtain a high correlation while being systematically wrong about every persona. The results therefore concern PVQ response stability under this protocol, not evidence for internal values.
With fictional personas, the highest mean rank-order result is Mixtral-8x7B-Instruct (r=0.43), followed by its 4-bit variant (0.30), Mistral-7B-Instruct-v0.2 (0.28), Qwen-72B (0.24), and GPT-3.5-1106 (0.20). With real-world personas, Mixtral-Instruct reaches 0.50 and Qwen-72B 0.46. Llama-2 and Phi models remain near zero. Without personas, ipsative stability is higher: Mixtral-Instruct reaches 0.84, its quantized variant 0.82, Qwen-72B 0.73, and Zephyr 0.62. This does not establish human equivalence: the human references describe longitudinal change over years, whereas the model scores correlate synthetic answers after topic changes. The authors themselves restrict the comparison to identifying models clearly below those references.
In the only conversation-length experiment, conducted with Mixtral-8x7B-Instruct and fictional characters, rank-order stability falls from 0.42 at three messages to 0.15 at 43, while ipsative stability stays high. The neutral-profile analysis suggests convergence toward a default profile: preserving within-person ordering is not the same as preserving differentiated identities. Three author-created behavioral tasks partly reproduce the family ranking but have very different ceilings. Religion is the most stable (maxima of 0.66–0.68), Donation is moderate (maximum 0.31), and Stealing reaches only 0.16. Expected PVQ–Donation directions appear for Universalism, Benevolence, Power, and Achievement, but none of the correlations exceeds 0.3.
The paper's strongest contribution is methodological: it demonstrates why a minimal-context psychological score cannot by itself characterize later behavior and separates interpersonal from intrapersonal stability. The comparative evidence is nevertheless exploratory. Topics, personas, and tasks are convenience samples; contexts are generated by the tested model family; sampling configurations differ across families; PVQ measurement structure is not validated for LLMs; and explanations involving scale, data, SFT, DPO, RLHF, quantization, or alignment are observational and confounded. The code audit also finds independent-sample t-tests applied to matched units, raw averaging of Spearman correlations, and a BH implementation that includes 21 diagonal entries in addition to the 210 declared pairwise comparisons. The official v1.0 tag contains neither data nor results; the later repository restores input stimuli but still lacks model outputs. The study therefore supports strong contextual sensitivity and descriptive checkpoint differences under this protocol. It does not establish internal values, training causality, general behavioral stability, or independent reproducibility of the published numbers.