{"id":"954742df-9303-428e-8ae3-3ce2ea89fa87","arxiv_id":"2606.06870","paper_version":2,"verdict":"UNVERDICTED","confidence":"LOW","novelty_score":4.0,"correctness_risk":"unknown","formal_verification":"none","parameter_count":0,"one_line_summary":"A 25-participant study finds that feedback on inferred goals improves intent alignment and reduces interventions in vision-based shared autonomy, with visual feedback preferred and information richness effects varying by task.","lead":"This paper examines how visual versus auditory feedback and sparse versus rich information about a robot's inferred goals affect user coordination and trust in shared autonomy systems. The user study results suggest practical interface design choices that could make assistive robots easier to work with.","discovery_kind":"new_application","skeptic_critique":{"model":"grok-4.3","headline":"No significant objection identified","rationale":"Reader's weakest assumption correctly flags the translation from inference legibility to coordination gains. However, the abstract already frames the results as evidence for that mechanism via the modality and richness manipulations, and no further internal flaw in that chain is detectable without contradicting the reported outcomes. The low reader confidence stems from abstract-only access rather than an argument defect.","tokens_in":1668,"tokens_out":215,"duration_ms":12306,"concrete_test":"Re-run the primary alignment and intervention metrics from the N=25 study after adding a non-inferential feedback control arm (e.g., generic status tones unrelated to goal inference); if the improvement disappears, the legibility mechanism requires qualification.","verdict_should_be":"UNCHANGED","load_bearing_attack":"The abstract and reported study design directly test the effect of feedback on intent alignment and intervention rates across modalities and information richness levels. The central claim follows from the observed significant improvements and task-dependent preferences without evident internal contradictions in the stated hypotheses or conclusions.","agreement_with_reader":"agree"},"referee_report":{"model":"grok-4.3","summary":"The manuscript reports results from a user study (N=25) examining how interface transparency designs—feedback modality (visual vs. auditory) and information richness (sparse vs. rich, including full belief distribution)—affect coordination, intent alignment, corrective interventions, and trust in a vision-based shared autonomy system for two assistive manipulation tasks. It claims that providing feedback yields statistically significant gains in alignment and reduced interventions, that visual feedback is preferred, that sparse/rich preferences are task-dependent, and that full belief distribution does not consistently help; design guidelines are derived from these observations.","tokens_in":1706,"tokens_out":477,"duration_ms":16528,"significance":"If the empirical results are supported by complete statistical reporting and controls, the work offers concrete, task-sensitive evidence that legible goal inference via feedback improves shared-control coordination more effectively than maximal disclosure. This directly informs practical interface design for assistive robots and contributes empirical grounding to transparency research in HRI.","major_comments":[{"comment":"Abstract and (presumably) §4/§5: the claim of statistically significant improvements in intent alignment and reduced interventions is presented without details on the specific tests, effect sizes, confidence intervals, exclusion criteria, or raw data distributions. With N=25 this information is load-bearing for evaluating whether the central claim about feedback benefits holds.","section":"Abstract"},{"comment":"Results section (task-dependent findings): the observation that full belief distribution did not consistently improve alignment or trust is central to the guideline that 'maximal disclosure' is not required, yet the manuscript provides no quantitative breakdown of per-task belief-distribution effects or power analysis to support the 'not consistently' conclusion.","section":"Results"}],"minor_comments":[{"comment":"Clarify how 'intent alignment' is operationalized (e.g., distance to ground-truth goal, intervention count, or subjective rating) and ensure this definition is used consistently when comparing modalities.","section":null},{"comment":"Figure captions and legends should explicitly state whether error bars represent standard error, 95% CI, or SD, and whether statistical significance markers are corrected for multiple comparisons.","section":null}],"recommendation":"major_revision","confidential_remarks":null},"author_rebuttal":{"model":"grok-4.3","summary":"We thank the referee for the constructive feedback emphasizing statistical transparency and granularity. We will revise the manuscript to provide the requested details on tests, effect sizes, and per-task breakdowns while maintaining the core claims supported by our N=25 study.","responses":[{"response":"We agree that full statistical reporting is necessary for evaluating the claims with N=25. In the revision we will add to §4/§5 (and reference in the abstract) the exact tests performed (e.g., paired t-tests or non-parametric equivalents), effect sizes, 95% confidence intervals, any participant exclusion criteria, and descriptive statistics or distribution summaries for the key metrics of intent alignment and corrective interventions.","revision_made":"yes","referee_comment":"[Abstract] Abstract and (presumably) §4/§5: the claim of statistically significant improvements in intent alignment and reduced interventions is presented without details on the specific tests, effect sizes, confidence intervals, exclusion criteria, or raw data distributions. With N=25 this information is load-bearing for evaluating whether the central claim about feedback benefits holds."},{"response":"We will expand the Results section with a quantitative per-task breakdown of belief-distribution effects, including means, SDs, and direct statistical comparisons between sparse and rich conditions for each task. A post-hoc power discussion will be added to address the 'not consistently' phrasing; we note that the original design relied on pilot data rather than a priori power analysis, which we will acknowledge as a limitation.","revision_made":"partial","referee_comment":"[Results] Results section (task-dependent findings): the observation that full belief distribution did not consistently improve alignment or trust is central to the guideline that 'maximal disclosure' is not required, yet the manuscript provides no quantitative breakdown of per-task belief-distribution effects or power analysis to support the 'not consistently' conclusion."}],"tokens_in":1330,"tokens_out":410,"duration_ms":12528,"standing_objections":[]},"desk_editor":{"model":"grok-4.3","letter":"The paper's core result is that making the robot's intent inference visible to users improves alignment and reduces corrective actions in vision-based shared autonomy for assistive tasks. Visual feedback beats auditory, and whether sparse or rich information is better depends on task complexity; showing the full belief distribution did not reliably help.\n\nThe study with N=25 participants across two manipulation tasks directly compares feedback modality and information richness. This is a straightforward empirical extension of existing transparency work in HRI, and the finding that legibility of the inferred goal drives the gains rather than maximal disclosure is useful for interface design.\n\nThe results line up with what the hypotheses predict and the abstract reports statistically significant improvements. That said, the abstract gives no details on the tests used, effect sizes, exclusion rules, or raw data, so the strength of the claims is hard to judge from what's here. N=25 is modest for drawing firm guidelines about real assistive robots.\n\nThis is for people building interfaces for shared-control assistive systems who want concrete comparisons on feedback choices. A reader focused on practical HRI guidelines could pull some value from the modality and richness results.\n\nIt should go to peer review so the methods and statistics can be checked properly.","headline":"Feedback on the robot's inferred goal improves coordination and cuts interventions in shared autonomy, with visual preferred over auditory.","tokens_in":2187,"tokens_out":313,"would_cite":false,"duration_ms":12282,"reading_group":"maybe","serious_thinker":"yes","would_accept_peer_review":true},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":[],"model":"grok-4.3","headline":"Feedback on inferred robot goals improves intent alignment in shared autonomy.","keywords":["shared autonomy","transparent interfaces","intent inference","assistive robotics","user study","feedback modality","trust"],"falsifier":"A replication where adding feedback on inferred goals produces no reduction in corrective interventions or no improvement in alignment.","tokens_in":2584,"feed_emoji":"🤖","tokens_out":495,"duration_ms":24890,"temperature":0.7,"pith_summary":"This paper tests how different feedback designs help users understand what an assistive robot is trying to do during shared control. It compares visual and auditory feedback, as well as sparse and rich information displays, in a study with 25 participants performing manipulation tasks. The key finding is that any feedback on the inferred goal helps users align their actions better and correct the robot less often. Visual feedback is generally preferred, and the amount of detail that helps depends on how complex the task is, while showing the full set of possible goals does not always lead to better results.","feed_headline":"Feedback on robot intent cuts corrective actions","feed_subtitle":"Making inferred goals visible improves alignment in assistive manipulation tasks","key_machinery":"Feedback designs that make the robot's inferred goal legible through visual or auditory interfaces in vision-based shared autonomy.","core_discovery":"Providing feedback on the robot's inferred goal significantly improves intent alignment and reduces corrective intervention. Participants preferred visual over auditory feedback, while preferences for sparse versus rich information depended on task complexity. Revealing the full belief distribution did not consistently improve alignment or trust.","pith_inferences":["Transparency guidelines could extend to other shared control applications like driving assistance.","Adaptive interfaces that adjust detail based on user experience might further improve outcomes.","Future work could test if these effects hold when inference accuracy is lower."],"forward_implications":["Feedback accelerates convergence to shared goals by making inference legible.","Visual feedback is preferred to auditory feedback across tasks.","Optimal information richness varies with task complexity.","Maximal disclosure of the belief distribution is not required for effective coordination or trust."],"fun_headline_variants":["Intent feedback cuts corrective interventions","Visual cues improve robot goal alignment","Sparse feedback aids coordination in tasks","Full belief views fail to boost user trust","Task complexity shapes feedback preferences"],"cache_read_input_tokens":2112,"weakest_assumption_plain":"Mismatches between the robot's inferred goals and the user's intended goals are the main source of friction in coordination.","fun_headline_variants_meta":{"raw":{"variants":["Intent feedback cuts corrective interventions","Visual cues improve robot goal alignment","Sparse feedback aids coordination in tasks","Full belief views fail to boost user trust","Task complexity shapes feedback preferences"]},"model":"grok-4.3","cost_usd":0.003209,"raw_usage":{"total_tokens":1686,"prompt_tokens":590,"num_sources_used":0,"completion_tokens":54,"cost_in_usd_ticks":32087000,"prompt_tokens_details":{"text_tokens":590,"audio_tokens":0,"image_tokens":0,"cached_tokens":256},"completion_tokens_details":{"audio_tokens":0,"reasoning_tokens":1042,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"tokens_in":590,"tokens_out":54,"duration_ms":8334,"temperature":1.0,"reasoning_tokens":1042,"cache_read_input_tokens":256,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-06-27T22:04:51.604800+00:00","model_set":{"reader":"grok-4.3"},"falsifier":"A replication where adding feedback on inferred goals produces no reduction in corrective interventions or no improvement in alignment.","supporting_citations":[],"review_version":1}