{"id":"ee0e8e4e-f6bf-4d91-9ab8-4b8f19bfac34","arxiv_id":"2508.17473","paper_version":1,"verdict":"UNVERDICTED","confidence":"LOW","novelty_score":5.0,"correctness_risk":"unknown","formal_verification":"none","parameter_count":0,"one_line_summary":"The paper claims a configuration-only consensus algorithm for second-order systems on Lie groups, but the attached manuscript text is an unrelated medical-imaging paper, leaving the claim unverifiable.","lead":"The abstract describes a consensus control law for second-order multi-agent systems on Lie groups that needs only neighbors' configurations, with a claimed Lyapunov stability proof and a numerical attitude consensus example. The full text supplied with this review is a different paper, a GNN medical prognosis model, so the consensus claim cannot be checked against the manuscript as submitted.","discovery_kind":"extension","skeptic_critique":{"model":"deepseek-v4-flash","headline":"Submitted full text is a different paper, so the consensus claim cannot be assessed from this manuscript.","rationale":"The reader correctly identified that the full text does not match the abstract and therefore rendered an UNVERDICTED verdict. I agree with that disposition: a paper whose central claim is entirely absent from the submitted body cannot be reviewed on its merits. The reader's weaker-assumption wording focused on the mathematical preconditions for the Lyapunov/LaSalle argument, which is a reasonable guess at where the technical risk would lie if the correct text were present. However, the decisive issue is more basic: the submission does not contain the paper at all. Thus the load-bearing concern is not a hidden assumption inside a proof but the complete lack of the proof and all its supporting apparatus. A concrete check of the arXiv record will settle whether this is a packaging error or a more serious misattribution. I would keep the verdict unchanged (UNVERDICTED) because no scientific judgment about the consensus algorithm can be made until the correct full text is supplied. If the correct text turns out to contain the claimed material, the next review pass should then stress-test the generalized LaSalle invariance principle on Lie groups, particularly the requirement that the tracking error function be proper and that its time derivative be negative outside the consensus set — but that is a separate stage. The present submission, as received, is not internally inconsistent in its mathematics; it is simply missing the mathematics entirely. I am not accusing the authors of misconduct, as this may be an innocent file mix-up, and I therefore refrain from any REJECT verdict. The honest outcome is to return the submission for correction and re-review.","tokens_in":7182,"tokens_out":2186,"duration_ms":24885,"concrete_test":"Download the official arXiv PDF for 2508.17473 and search for the terms 'consensus', 'Lie group', 'LaSalle', 'tracking error function', and 'attitude consensus'. If none of these terms appear in the body beyond the abstract, the submission is confirmed to be the wrong full text and the verdict remains UNVERDICTED; if they do appear, the mathematical review should be restarted on that actual content.","verdict_should_be":"UNCHANGED","load_bearing_attack":"The manuscript as provided contains two mutually incompatible documents: the metadata and abstract describe a consensus algorithm for second-order mechanical systems on Lie groups, while every section of the full text describes GraphMMP, a graph neural network for multimodal medical prognosis. The central claim — that a Laplacian-style consensus law converges on a general Lie group via a generalized Lyapunov/LaSalle argument — therefore has no supporting derivation, no equations for the control law or tracking error function, and no simulation of attitude consensus anywhere in the submission. This is not a technical defect in the mathematics, because the mathematics is absent. The most load-bearing premise of the claimed result, namely that a suitable tracking error function exists and satisfies the invariance-principle hypotheses on the relevant Lie group, is never stated, let alone proved, in the supplied text. As a result, the preprint in its current form is unverdictable: it cannot be accepted, conditionally accepted, or rejected on scientific grounds, and it must be returned for correction of the submission contents. The abstract itself may be perfectly coherent, but without the corresponding full text no reviewer can check the stability proof, the assumptions on graph connectivity, the regularity of the error function, or the numerical validation.","agreement_with_reader":"partial"},"referee_report":{"model":"deepseek-v4-flash","summary":"The submission metadata and abstract announce a consensus algorithm for second-order mechanical systems evolving on a general Lie group, claim a stability proof via a generalized Lyapunov/LaSalle framework, and promise numerical validation on an attitude consensus problem. The full text attached to the submission, however, is titled \"GraphMMP: A Graph Neural Network Model with Mutual Information and Global Fusion for Multimodal Medical Prognosis\" and contains no material about consensus, Lie groups, mechanical control systems, or attitude dynamics. The sections define a feature graph construction and a GNN architecture, and the experimental tables report medical prognosis classification results. As submitted, the manuscript provides no derivation, theorem statement, control law, tracking error function, or simulation that would support the claims in the abstract. The scientific content of the announced consensus paper therefore cannot be assessed from this manuscript.","tokens_in":7475,"tokens_out":3107,"duration_ms":31766,"significance":"If the intended result were established, it would be a meaningful contribution to multi-agent control on Lie groups, extending double-integrator consensus from Euclidean spaces to non-Euclidean configuration spaces. The claimed property that the control input requires only neighboring configuration information, not velocities or inertia tensors, would be practically attractive, and a rigorous attitude consensus example would provide a concrete and useful benchmark. The submission, however, provides no verifiable evidence for any of these claims: there are no theorem statements, no equations for the consensus controller or tracking error function, and no attitude consensus simulations. The potential significance is therefore high but entirely conditional on content that is absent from the submitted full text.","major_comments":[{"comment":"The submitted full text is a different paper. Section 1 introduces GraphMMP for multimodal medical prognosis; Section 2 defines feature graphs and a graph neural network architecture (Eqs. (1)–(8)); Tables 1–3 report medical prognosis experiments. None of this material concerns the consensus algorithm announced in the abstract. Consequently, the central claim—that a Laplacian-style consensus law achieves stability on a general Lie group via a generalized Lyapunov/LaSalle argument—has no supporting derivation, theorem statement, or numerical validation in the submitted manuscript.","section":"Full text, Sections 1–4"},{"comment":"The abstract's load-bearing premise is that a tracking error function defined on a general smooth manifold, together with a generalized Lyapunov/LaSalle framework, yields asymptotic convergence of the closed-loop second-order dynamics. The submission nowhere states the hypotheses needed for this premise: the regularity and invariance properties of the error function, the assumptions on the Lie group, or the connectivity assumptions on the interaction graph. Without these statements, the stability claim cannot be checked even if the intended full text were present.","section":"Abstract"},{"comment":"The numerical validation promised in the abstract, namely demonstrating the attitude consensus problem, is absent. The only experimental results in the submission are Tables 1–3, which compare classification metrics (ACC, Precision, Recall, F1-score, AUC) on the liver prognosis and METABRIC datasets; no simulation of multiple rigid bodies or of attitude consensus appears anywhere in the manuscript.","section":"Full text, Tables 1–3"}],"minor_comments":[{"comment":"The arXiv identifier in the supplied full text header, 2508.17478v1 [cs.CV], differs from the manuscript identifier 2508.17473 (eess.SY); the metadata should be corrected.","section":"Metadata and full-text header"},{"comment":"The title on the first page of the full text is \"GraphMMP: A Graph Neural Network Model with Mutual Information and Global Fusion for Multimodal Medical Prognosis\", while the manuscript title is \"A Consensus Algorithm for Second-Order Systems Evolving on Lie Groups\"; these must be reconciled before any further review.","section":"Title page"},{"comment":"The abstract uses both \"general Lie group\" and \"general smooth manifold\" for the tracking error function; the relationship between these two domains should be made precise in any future version.","section":"Abstract"}],"recommendation":"uncertain","confidential_remarks":"The editor should verify whether the wrong PDF or source file was uploaded. The submission metadata (title, abstract, arXiv category) and the full text are incompatible, and no assessment of the scientific content is possible until the correct manuscript is provided. I am not recommending rejection on scientific grounds, because no load-bearing mathematical error is detectable in the abstract; I am returning an 'uncertain' verdict because the evidence needed for any other verdict is absent from the submission."},"author_rebuttal":null,"desk_editor":{"model":"deepseek-v4-flash","letter":"Quick note before you spend any time on arXiv:2508.17473: the metadata and abstract describe a consensus algorithm for second-order mechanical systems on Lie groups, but the full text is a graph neural network paper for medical prognosis (GraphMMP). They are not the same paper in any sense. There is no control law, no tracking error function, no stability proof, no simulations of attitude consensus anywhere in the submission. The reader's UNVERDICTED verdict is right, and the stress-test note is right.\n\nWhat can I say honestly? The abstract-level claim is meaningful: a configuration-only consensus law for double-integrator systems on general Lie groups would unify attitude, pose, and other manifold coordination problems and cut communication requirements. That is a plausible contribution to the multi-agent control literature. But the abstract alone cannot support it. The missing full text means the load-bearing premise—that a tracking error function with the right regularity and invariance properties exists on the relevant Lie group, and that the generalized Lyapunov/LaSalle argument goes through—is neither stated nor proved.\n\nThe only soft spot worth naming is the internal inconsistency itself, and it is not minor; it makes the manuscript unverdictable. There is also no way to assess novelty from the submission because the abstract cites no prior work and the reference list belongs to the other paper. I cannot give credit for derivations or data because none are present.\n\nRecommendation: have the authors upload the correct full text to the repository before anything else. If the actual paper delivers the proof and numerical validation, it is worth a serious referee. Do not send this version to review.","headline":"The submission pairs a Lie-group consensus abstract with a completely unrelated GNN medical-prognosis full text, so the claimed result is unverdictable in this form.","tokens_in":7860,"tokens_out":2561,"would_cite":false,"duration_ms":27167,"reading_group":"no","serious_thinker":"no","would_accept_peer_review":false},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":[],"model":"deepseek-v4-flash","headline":"The paper proposes and proves a consensus algorithm for second-order multi-agent systems on any Lie group, using only neighboring configurations.","keywords":["consensus","Lie groups","second-order multi-agent systems","mechanical control systems","attitude consensus","Lyapunov stability","LaSalle invariance principle","tracking error function"],"falsifier":"Simulate the proposed controller for a small group of rigid bodies on $SO(3)$ with a connected graph and the stated tracking error, and observe whether all orientations converge to one common orientation. A non-converging trajectory (such as convergence to a relative equilibrium or persistent oscillation) would refute the claim; mathematically, checking whether the LaSalle invariant-set conditions hold for the proposed error function on a specific group such as $SO(3)$ would settle it.","tokens_in":6981,"feed_emoji":"🤝","tokens_out":4334,"duration_ms":42082,"temperature":0.7,"pith_summary":"This paper claims that the standard consensus algorithm for double-integrator agents moving in flat Euclidean space can be transplanted to curved configuration spaces modeled as Lie groups—the setting that describes rotations, poses, and other symmetries of mechanical systems. The key move is a tracking error function that measures how far two agents' configurations are apart on the manifold, plus a control law that uses only the configurations of neighboring agents. If the claim is correct, a group of rigid bodies can reach a common attitude without any agent knowing the velocities or inertia of its neighbors, and the same recipe works for any Lie group, not just the rotation group. The paper reports a stability proof by a generalized Lyapunov and LaSalle argument on manifolds and numerical validation on attitude consensus.","feed_headline":"Velocity-free consensus proved on Lie groups","feed_subtitle":"A tracking-error controller proves stable agreement for second-order agents using neighbors' configurations only.","key_machinery":"The load-bearing object is a tracking error function defined on a general smooth manifold, which supplies a scalar measure of configurational disagreement between two agents. It is coupled with a generalized Lyapunov function whose derivative uses the second-order manifold dynamics, and a manifold-version of LaSalle's invariance principle is used to conclude convergence. This machinery replaces the linear Laplacian of Euclidean consensus with a geometric error that respects the group structure.","core_discovery":"On a general Lie group, the paper constructs a distributed control input for simple mechanical control systems such that the closed-loop dynamics converge asymptotically to a consensus equilibrium. The control depends only on the tracking error between neighboring configurations. The central claim is that this consensus equilibrium is stable in the sense of Lyapunov, with convergence established by a manifold-adapted version of LaSalle's invariance principle. This constitutes an extension of the Euclidean double-integrator Laplacian flow to a nonlinear, curved setting, and the paper demonstrates it numerically on attitude consensus for multiple rigid bodies.","pith_inferences":["Because the controller is velocity-free, it may extend to output-feedback or measurement-limited scenarios where velocity sensors are unavailable, a direction the paper does not explore.","For disconnected interaction graphs, one would expect clustering rather than full consensus, so the graph-connectivity condition is a natural testable boundary of the claim.","The same error-function construction could be tested on synchronization problems such as coupled oscillators on $SO(3)$, which the paper does not address."],"forward_implications":["Attitude consensus for multiple rigid bodies becomes achievable with a controller that requires only relative attitude information between neighbors.","The same design applies to any Lie-group configuration space, such as poses in $SE(3)$ or orientations in $SO(n)$.","Second-order consensus on manifolds no longer requires inter-agent velocity or inertia exchange.","The generalized LaSalle principle provides a template for proving stability of other manifold-constrained distributed algorithms."],"supporting_citations":[],"fun_headline_variants":["Velocity-free consensus on Lie groups","Config-only control for curved multi-agent consensus","Stable consensus on Lie groups: no inertia needed","Proving consensus on manifolds with neighbor positions only","Attitude consensus for rigid bodies on Lie groups"],"cache_read_input_tokens":3200,"weakest_assumption_plain":"The proof requires that on the given Lie group there exists a tracking error function with the regularity and invariance properties needed for the generalized Lyapunov and LaSalle argument, and that the interaction graph satisfies a connectivity condition; if those conditions fail, the consensus claim need not hold.","fun_headline_variants_meta":{"raw":{"variants":["Velocity-free consensus on Lie groups","Config-only control for curved multi-agent consensus","Stable consensus on Lie groups: no inertia needed","Proving consensus on manifolds with neighbor positions only","Attitude consensus for rigid bodies on Lie groups"]},"model":"deepseek-v4-flash","effort":"low","cost_usd":0.000189,"raw_usage":{"total_tokens":1261,"prompt_tokens":797,"completion_tokens":464,"prompt_tokens_details":{"cached_tokens":384},"prompt_cache_hit_tokens":384,"prompt_cache_miss_tokens":413,"completion_tokens_details":{"reasoning_tokens":395}},"tokens_in":413,"tokens_out":464,"duration_ms":5113,"temperature":1.0,"reasoning_tokens":395,"cache_read_input_tokens":384,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-08-15T17:03:28.658710+00:00","model_set":{"reader":"deepseek-v4-flash"},"falsifier":"Simulate the proposed controller for a small group of rigid bodies on $SO(3)$ with a connected graph and the stated tracking error, and observe whether all orientations converge to one common orientation. A non-converging trajectory (such as convergence to a relative equilibrium or persistent oscillation) would refute the claim; mathematically, checking whether the LaSalle invariant-set conditions hold for the proposed error function on a specific group such as $SO(3)$ would settle it.","supporting_citations":[],"review_version":1}