Such behavior can compound in realistic assistants that must switch between domains dynamically.For Entity Extraction, models correctly update some slots but are distracted by nearby mentions, overwriting the final reservation time. This illustrates how transient context interference disrupts working memory and undermines the reliability of structured information tracking over dialogue turns. Engaging with some of the process measures and surveys can also validate high reliability. Are we sustaining error-free, harm-free performance over a longer time horizon? Based on interviews with hospital executives, program leaders, staff, and physicians, the study found that nurses were often the targets of HRO interventions, which due to existing hierarchies led to piecemeal implementations. Thus, questions remain on how best to intervene to integrate all the HRO principles and on which HRO principles are most necessary for patient safety.
Further investigation is needed to determine if our findings hold in vision-language models relying on imaging and radiology reports for example. Reliability in research is the extent to which a measurement procedure produces consistent scores under conditions in which the characteristic being measured has not genuinely changed. Researchers evaluate reliability across time, items, raters or equivalent forms. High reliability indicates limited random measurement error, but it does not prove that a measure is valid or accurate.
Second, while Kim et al. focus on switching from a correct or incorrect answer option, we evaluate a model’s ability to maintain a safe abstention when no correct options are present, and subsequently transition from that abstention when the correct option is introduced. Finally, we move beyond proprietary models to systematically evaluate the effect of parameter scaling on open-weight model families from 1B to 72B. Motivated by real-world scenarios where users naturally build and refine their thoughts over the course of a conversation, recent work has begun evaluating how sycophantic tendencies affect LLM reliability across multi-turn dialogue. Notably, Laban et al. demonstrated that in underspecified regimes, models make premature assumptions which compound over subsequent turns of conversation Laban et al. (2025). In another study, Hong et al. introduced SyconBench, a multi-turn sycophancy benchmark that evaluates model resilience to increasing pressure from a user to comply to unethical requests and false presuppositions Hong et al. (2025). This work also formalized the Turn of Flip (ToF) metric to quantify the conversational turn at which a model abandons its initial stance.
If the two results are very different, this indicates low internal consistency. A group of participants complete https://thisromances.com/ a questionnaire designed to measure personality traits. If they repeat the questionnaire days, weeks or months apart and give the same answers, this indicates high test-retest reliability.
Teams we spoke with were looking for better visibility into maintenance operations, inspections, and reliability data without making workflows harder for the people managing them every day. Those conversations naturally led to discussions about the DMSI Reliability Package and how organizations can begin improving reliability processes in ways that feel practical and manageable for their teams. A questionnaire can have high internal consistency while the study’s central finding fails to replicate. Conversely, a replicable population effect can be investigated with measures that still contain some measurement error. If a patient’s score improves by three points but the smallest detectable change is seven points, the researcher cannot confidently conclude that the change exceeds measurement error.
Appendix M Recap & Snowball Experiment Implementation
- A scale that measures test anxiety includes questions about how often students feel stressed when taking exams.
- Research conclusions depend on the quality of the measurements used to produce them.
- Simulates a Sharded conversation, and adds a final recapitulation turn which restates all the shards of the instruction in a single turn, giving the LLM one final attempt at responding.
- Conversely, a replicable population effect can be investigated with measures that still contain some measurement error.
- We hypothesize that this is due to the model making incorrect assumptions in premature solutions, which conflict with subsequent user instructions in later turns.
If they first agree on every category through discussion and then calculate agreement, the resulting value no longer represents independent inter-rater reliability. For continuous scores, an appropriately specified intraclass correlation coefficient is often preferable to Pearson’s correlation when agreement is important. Measurement error can weaken observed correlations and make effects more difficult to detect. Low reliability may therefore reduce statistical power and distort regression coefficients or group comparisons.
Healthcare Leadership
To bridge this gap, SoS transforms static question-answer spaces into multi-turn conversational exchanges, representing each answer option as an alternative hypothesis (Figure 1). By forcing models to navigate these sequential decision spaces, this framework quantifies an LLM’s resilience against conversational pressure and user suggestions. Notably, this approach can be adapted to any existing question-answer benchmark, and relies only on the (in)correct labels provided in datasets.
Parallel-forms reliability compares two different versions of the same test, such as two IQ-test forms with different questions but matched difficulty. Sijtsma argued researchers should report alpha alongside a factor analysis of the scale’s structure. He also recommended newer statistics, such as McDonald’s omega, when alpha’s assumptions do not hold. Values range from 0 to 1, with higher values indicating greater internal consistency.
Appendix C Statistical Significance Tests
We note that though a more recent iteration of BFCL includes multi-turn instructions, it differs from sharding experiments as it does not involve underspecification, with each turn having an independent intermediate solution (which we call episodic multi-turn conversations). Our implementation in comparison shards original instructions allowing us to simulate multi-turn underspecified conversations for this task setting. The Background section (Section 2) discusses the relationship between episodic and underspecified multi-turn conversation more in-depth.