arXiv subjects

Tianyi Yang

Publications and source records attributed to Tianyi Yang.

At least 19 recordsLinked to original sources

arXiv2026

PosterHarness: Turning Scientific Poster Generation into an Auditable Instruction-Following Benchmark

Text-rich image models can now design poster-scale layouts, but we lack ways to measure whether they honor scientific communication contracts: legible labels, prescribed aspect ratios, and -- above all -- abstaining from fabricated scientific figures. We present POSTERHARNESS, an auditable harness reframing poster generation as measurable instruction-following tasks, with a pilot benchmark and failure taxonomy. POSTERHARNESS uses a placeholder-first contract to separate two jobs models otherwise conflate. The model performs visual-summary design: typography, reading path, color, and background -- but never draws data-bearing figures. Every figure region must be an empty labeled placeholder; a deterministic compositor inserts real source-paper figures at detected coordinates. This makes properties measurable: placeholder count and ID accuracy, blankness, aspect-ratio compliance, abstention from synthesized graphics, public-text hygiene, and source-figure provenance -- with failures logged as explicit rejections, not hidden in plausible-looking output. We instantiate the harness on 12 papers (6 HEP, 6 AI/ML-adjacent) and report three findings. (i) A counterfactual probe shows the placeholder contract drives VLM-counted synthesized figures from 34 to 0 across three papers. (ii) A failure taxonomy identifies blocking contracts: placeholder geometry, placeholder QA, template critic, and public text. (iii) Comparison with Paper2Poster shows a trade-off: PosterHarness yields higher-resolution artifacts, lower white-canvas fraction, and stronger VLM visual preference; the deterministic baseline retains slightly more PosterQuiz-style information and runs faster. We report this as regime characterization, not a superiority claim. All artifacts, prompts, manifests, and audit scripts are released as a reusable evaluation component.

cs.CV↗

arXiv2026

Agentic Hybrid RAG for Evidence-Grounded Muon Collider Analysis

Muon collider research spans accelerator physics, detector instrumentation, and high-energy phenomenology, with relevant evidence scattered across a rapidly expanding and heterogeneous body of scientific literature. As high-energy physics (HEP) increasingly explores agent-assisted analysis workflows, efficiently locating, integrating, and verifying scientific evidence becomes an essential capability. While retrieval-augmented generation (RAG) offers a promising framework for scientific question answering, integrating agentic reasoning without compromising retrieval precision remains a key challenge. In this work, we present agentic hybrid RAG, an evidence-grounded RAG framework for muon collider research. The framework combines a hybrid retriever, integrating sparse lexical and dense semantic retrieval, with an agentic reasoning module for query decomposition, evidence expansion, and grounded answer generation. To enable systematic evaluation, we construct the first benchmark for retrieval-augmented scientific question answering in the muon collider domain, comprising a curated literature corpus together with dedicated retrieval and answer-generation benchmarks covering major detector and physics research topics. Extensive evaluation shows that hybrid retrieval provides the strongest retrieval backbone, while agentic reasoning is most effective for controlled evidence expansion and answer synthesis. Built on this principle, agentic hybrid RAG consistently outperforms representative retrieval and RAG baselines in retrieval effectiveness, answer quality, evidence coverage, and factual grounding. Together, the benchmark and framework provide a foundation for evidence-grounded scientific question answering and future HEP analysis agents operating over large-scale scientific literature.

hep-ex↗

arXiv2026

"Hadron-in-fat-jet'' AI Tagging to Detect Rare Decays Such as $W^{\pm}\to\pi^{\pm}\gamma$

We investigate a novel class of boosted-object signatures at the LHC, where a high-$p_{\text{T}}$ fat-jet contains an identifiable hadron or quarkonium state originating from rare or semi-exclusive decays. Unlike conventional boosted jet studies, which focus on multi-prong partonic substructure, our approach probes hybrid configurations such as $W^{\pm}\to\pi^{\pm}\gamma$, where a localized hadronic or quarkonium signal is embedded within a collimated jet. By fine-tuning the signature-oriented, pre-trained Sophon AI model optimized for large-radius jets, and combining it with an event-level BDT and a soft-drop-mass shape fit, we obtain an expected 95\% CL upper limit of ${\cal B}(W^{\pm}\to\pi^{\pm}\gamma)<2.78\times10^{-5}$ for $450\,\mathrm{fb}^{-1}$ in our nominal setup. This study serves as a first proof-of-principle demonstration of the ``hadron-in-fat-jet'' paradigm; substantial gains in sensitivity are expected from improved trigger strategies, additional production channels, and dedicated taggers, while the methodology itself is broadly applicable to a wide range of rare Standard Model processes and searches for light or exotic resonances at present and future collider experiments.

hep-ph↗

arXiv2026

FLAMINGO: The thermal history of the Universe from tSZ effect cross-correlations and its dependencies on cosmology and baryon physics

The cross-correlation between tracers of large-scale structure, such as galaxies or quasars, and the thermal Sunyaev-Zel'dovich (tSZ) signal yields a measure of the bias-weighted mean electron pressure, $\langle b_\mathrm{h} P_\mathrm{e} \rangle$, where $b_\mathrm{h}$ is the halo bias and $P_\mathrm{e}$ is the electron pressure. With a model for the bias, one can derive the thermal history, $\mathrm{d}y/\mathrm{d}z$, where $y$ is the Compton parameter and $z$ is redshift. We explore how these quantities depend on redshift, cosmology, and the physics of galaxy formation using the FLAMINGO suite of cosmological hydrodynamical simulations, which spans a range of cosmological parameters and baryonic feedback implementations in volumes of up to $(2.8\,\text{Gpc})^3$. We find that $\langle b_\mathrm{h} P_\mathrm{e} \rangle$ depends steeply on $S_8 \equiv \sigma_8\sqrt{\Omega_\mathrm{m}/0.3}$, with an effective scaling $\langle b_\mathrm{h} P_\mathrm{e} \rangle \propto S_8^{\epsilon(z)}$, where the exponent $\epsilon(z) \approx 3$ over the redshift range $0.1 \leq z \leq 1$. Compared with existing cross-correlation measurements using tracer samples from SDSS, BOSS, eBOSS, DES, and DESI cross-correlated with tSZ measurements from Planck, we find that models with a low-$S_8$ cosmology and strong feedback are preferred, with a joint fit yielding $S_8 = 0.72^{+0.03}_{-0.03}$ and a normalised group-mass halo baryon fraction $f_b(10^{13}\,M_\odot, z=0.1)/(\Omega_b/\Omega_m) = 0.10^{+0.09}_{-0.05}$ . Contrary to most probes of feedback which sample smaller scales (e.g., X-ray measurements), we show that feedback boosts $\langle b_\mathrm{h} P_\mathrm{e} \rangle$, thus providing a novel test of feedback models. Overall, our results show the thermal history provides a route to jointly constrain cosmological parameters and test models of galaxy formation.

astro-ph.CO↗

arXiv2026

Beyond Isolation: A Unified Benchmark for General-Purpose Navigation

The pursuit of general-purpose embodied agents is hindered by fragmented evaluation protocols that isolate navigation skills and fixate on specific robot morphologies, failing to reflect real-world scenarios where agents must orchestrate diverse behaviors across varying embodiments. To bridge this gap, we introduce OmniNavBench, a benchmark for cross-skill coordination and cross-embodiment generalization. OmniNavBench introduces three paradigm shifts: (1) Compositional Complexity. We propose composite instructions that interleave sub-tasks from 6 categories (PointNav, VLN, ObjectNav, SocialNav, Human Following and EQA), compelling agents to transition between exploration, interaction, and social compliance within a single episode. (2) Morphological Universality and Sensor Flexibility. We present a simulation platform that breaks the reliance on single-morphology evaluation, enabling generalization tests across humanoid, quadrupedal, and wheeled robots, with a modular sensor interface and 170 environments blending synthetic assets with real-world scans. (3) Demonstrations Quality. Moving beyond shortest-path algorithms, we curate 1779 expert trajectories via human teleoperation, capturing behavioral nuances such as exploratory glance and anticipatory avoidance. Extensive evaluations demonstrate that current methods, despite their claimed unified design, struggle with the complex, interleaved nature of general-purpose navigation. This exposes a critical disparity between existing capabilities and real-world deployment demands, underscoring OmniNavBench as a testbed for the next generation of generalist navigators. Dataset, code, and leaderboard are available at http://omninavbench.cloud-ip.cc.

cs.RO↗

arXiv2026

The FLAMINGO simulations data release

We describe the public release of $>2.3$ petabytes of data from the FLAMINGO cosmological simulations. The suite consists of hydrodynamical simulations that include radiative cooling, star formation, stellar mass loss and the resulting chemical enrichment, supernova feedback, and two implementations of AGN feedback. Neutrinos are simulated explicitly using particles. Data products include snapshots, halo and galaxy catalogues, HEALPix all-sky lightcone maps, particle data for lightcone maps, and power spectra. The FLAMINGO set includes 22 hydrodynamical simulations. In addition, there are 16 gravity-only simulations, including the $10080^3$ particles FLAMINGO-10k run, with initial conditions that match those of the corresponding hydrodynamical runs. The fiducial hydrodynamical simulations span three numerical resolutions that have each been calibrated to reproduce the present-day galaxy stellar mass function and gas fractions in low-redshift clusters. Other simulations systematically vary the galaxy stellar mass function, cluster gas fractions, cosmology (including neutrino masses), and/or the nature of dark matter, in volumes of 1Gpc$^3$. The release includes hitherto unpublished simulations that use extra dark matter particles. While we provide a facility for downloading complete simulation outputs, we recognise that for many users this will not be possible due to limited local storage or network bandwidth. We implement a web service that enables users to explore available outputs and selectively download datasets or parts of datasets.

astro-ph.CO↗

arXiv2026

From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing

Simulation-based testing of autonomous driving systems (ADS) must uncover realistic and diverse failures in dense, heterogeneous traffic. However, existing search-based seeding methods (e.g., genetic algorithms) struggle in high-dimensional spaces, often collapsing to limited modes and missing many failure scenarios. We present PtoP, a framework that combines adaptive random seed generation with Stein Variational Gradient Descent (SVGD) to produce diverse, failure-inducing initial conditions. SVGD balances attraction toward high-risk regions and repulsion among particles, yielding risk-seeking yet well-distributed seeds across multiple failure modes. PtoP is plug-and-play and enhances existing online testing methods (e.g., reinforcement learning--based testers) by providing principled seeds. Evaluation in CARLA on two industry-grade ADS (Apollo, Autoware) and a native end-to-end system shows that PtoP improves safety violation rate (up to 27.68%), scenario diversity (9.6%), and map coverage (16.78%) over baselines.

cs.SE↗

arXiv2026

A measurement of gas rotation in galaxy groups via the kinetic Sunyaev-Zeldovich effect

We utilise the kinetic Sunyaev-Zeldovich effect (kSZ) to measure the rotation of ionised gas within galaxy groups defined in the SDSS-DR7 galaxy sample, via their dipolar imprint on the cosmic microwave background (CMB). We estimate the direction of the projected angular momentum for each group by measuring the redshift dipole of satellite galaxies around their group centre. We find a clear redshift dipole in the stacked data for the SDSS groups. We then perform oriented stacking of the Planck CMB temperature map using the group centres and directions of angular momenta. We report a $2.3\sigma$ measurement of the coherent rotational kSZ effect (rkSZ) within the virial radii of SDSS groups with an average mass of $10^{14}h^{-1} \rm M_{\odot}$. We estimate the averaged rotational velocity of the sample to be $\sim 100-200 ~\rm km ~s^{-1}$, peaking at approximately half the virial radius. Our results are consistent within the errors with predictions based on the ELUCID constrained realisation simulation, with the predicted amplitude of the rkSZ signal being slightly lower near the centre. We also identify a systematic bias when estimating rotational velocities using the observed redshifts of galaxies, but find it to be subdominant for our analysis.

astro-ph.CO↗

arXiv2026

Augmenting Question Answering with A Hybrid RAG Approach

Retrieval-Augmented Generation (RAG) has emerged as a powerful technique for enhancing the quality of responses in Question-Answering (QA) tasks. However, existing approaches often struggle with retrieving contextually relevant information, leading to incomplete or suboptimal answers. In this paper, we introduce Structured-Semantic RAG (SSRAG), a hybrid architecture that enhances QA quality by integrating query augmentation, agentic routing, and a structured retrieval mechanism combining vector and graph based techniques with context unification. By refining retrieval processes and improving contextual grounding, our approach improves both answer accuracy and informativeness. We conduct extensive evaluations on three popular QA datasets, TruthfulQA, SQuAD and WikiQA, across five Large Language Models (LLMs), demonstrating that our proposed approach consistently improves response quality over standard RAG implementations.

cs.CL↗

arXiv2025

Constraints on SMEFT operators from $Z \to \mu \mu bb$ decay

The Standard Model Effective Field Theory (SMEFT) provides a systematic framework to probe indirect effects of heavy new physics via precision measurements. While SMEFT constraints have been extensively studied using purely leptonic $Z$ decays and inclusive $Z$ production, mixed leptonic-hadronic modes remain largely unexplored. In this work, we analyze $Z \to \mu\mu bb$ decays within the SMEFT framework, deriving constraints on dimension-six operators that affect four-fermion interactions between leptons and bottom quarks, as well as $Z$-fermion couplings. Signal and background events are simulated with state-of-the-art Monte Carlo tools, including detector effects such as $b$-tagging, and limits on the relevant Wilson coefficients are extracted using kinematic distributions and a profile likelihood approach. Our results provide complementary constraints to existing SMEFT studies and yield the first process-specific limits on flavor-resolved four-fermion operators involving muons and bottom quarks from $Z$ decays.

hep-ph↗

arXiv2025

Self-consistent secondary cosmic microwave background anisotropies and extragalactic foregrounds in the FLAMINGO simulations

Secondary anisotropies in the cosmic microwave background (CMB) contain information that can be used to test both cosmological models and models of galaxy formation. Starting from lightcone-based HEALPix maps and catalogues, we present a new set of mock CMB maps constructed in a self-consistent manner from the FLAMINGO suite of cosmological hydrodynamical simulations, including CMB lensing, thermal and kinetic Sunyaev-Zeldovich effects, cosmic infrared background, radio point source and anisotropic screening maps. We show that these simulations reproduce a wide range of observational constraints. We also compare our simulations with previous predictions based on dark matter-only simulations which generally model the secondary anisotropies independently from one another, concluding that our hydrodynamical simulation mocks perform at least as well as previous mocks in matching the observations whilst retaining self-consistency in the predictions of the different components. Using the model variations in FLAMINGO, we further explore how the signals depend on cosmology and feedback modelling, and we predict cross-correlations between some of the signals that differ significantly from those in previous mocks. The mock CMB maps should provide a valuable resource for exploring correlations between different secondary anisotropies and other large-scale structure tracers, and can be applied to forecasts for upcoming surveys.

astro-ph.CO↗

arXiv2025

Prospects for measuring electroweak production of $Z\gamma\gamma$ and 2 jets at the LHC

Vector boson scattering (VBS) serves as a powerful channel for probing the Standard Model, particularly the electroweak symmetry breaking mechanism. Currently, studies of VBS mainly focus on $2 \to 2$ scattering. In this study, we investigate the $2\to 3$ VBS process of $\text{p p} \to Z\gamma\gamma + 2~\text{jets}$ through Monte Carlo simulations, including signal generation and background analysis. The signal significance is evaluated across different phase-space regions. With an integrated luminosity of 500 fb$^{-1}$, the signal significance can reach about 4.5 $\sigma$. These results suggest that, given the ongoing release of the LHC Run 3 dataset, there will be promising opportunities to explore and potentially discover a series of $2\to 3$ VBS processes, starting with the $Z\gamma\gamma$ channel.

hep-ph↗

arXiv2025

Human-Inspired Neuro-Symbolic World Modeling and Logic Reasoning for Interpretable Safe UAV Landing Site Assessment

Reliable assessment of safe landing sites in unstructured environments is essential for deploying Unmanned Aerial Vehicles (UAVs) in real-world applications such as delivery, inspection, and surveillance. Existing learning-based approaches often degrade under covariate shift and offer limited transparency, making their decisions difficult to interpret and validate on resource-constrained platforms. We present NeuroSymLand, a neuro-symbolic framework for marker-free UAV landing site safety assessment that explicitly separates perception-driven world modeling from logic-based safety reasoning. A lightweight segmentation model incrementally constructs a probabilistic semantic scene graph encoding objects, attributes, and spatial relations. Symbolic safety rules, synthesized offline via large language models with human-in-the-loop refinement, are executed directly over this world model at runtime to perform white-box reasoning, producing ranked landing candidates with human-readable explanations of the underlying safety constraints. Across 72 simulated and hardware-in-the-loop landing scenarios, NeuroSymLand achieves 61 successful assessments, outperforming four competitive baselines, which achieve between 37 and 57 successes. Qualitative analysis highlights its superior interpretability and transparent reasoning, while deployment incurs negligible edge overhead. Our results suggest that combining explicit world modeling with symbolic reasoning can support accurate, interpretable, and edge-deployable safety assessment in mobile systems, as demonstrated through UAV landing site assessment.

cs.RO↗

arXiv2025

The kinetic Sunyaev Zeldovich effect as a benchmark for AGN feedback models in hydrodynamical simulations: insights from DESI + ACT

Baryonic feedback remains one of the largest uncertainties in cosmological hydrodynamical simulations, with different prescriptions producing divergent predictions for the fraction of gas expelled from halos, the radial extent of the gas expulsion and the impact on large scale matter clustering. We present the first systematic study of the kinetic Sunyaev-Zel'dovich (kSZ) effect across a wide range of simulations (FLAMINGO, ANTILLES, BAHAMAS, SIMBA, FABLE and their variants), and compare them directly to DESI Year 1 + ACT kSZ measurements. We ensure a like-for-like comparison with observations by developing a robust methodology that accounts for the halo mass selection using galaxy-galaxy lensing, cosmic variance, miscentering and satellites, establishing the kSZ effect as a new benchmark for the simulations. We find that fiducial feedback models are disfavoured by >3 sigma, while simulations with more powerful AGN feedback within the FLAMINGO and BAHAMAS suites, as well as SIMBA, reproduce the observed kSZ signal within <2 sigma. We use the ANTILLES simulation suite to demonstrate that the amplitude of the kSZ effect is a strong predictor of matter power spectrum suppression, competitive with baryon fraction metrics. These results establish the kSZ as a critical probe for evaluating feedback physics and for advancing the fidelity of cosmological simulations.

astro-ph.CO↗

arXiv2025

UniSage: A Unified and Post-Analysis-Aware Sampling for Microservices

Traces and logs serve as the backbone of observability in microservice architectures, yet their sheer volume imposes prohibitive storage and computational burdens. To reduce overhead, operators rely on sampling; however, current frameworks generally employ a sample-before-analysis strategy. This approach creates a fundamental trade-off: to save space, systems must discard data before knowing its diagnostic value, often losing critical context required for troubleshooting anomalies and latency spikes. In this paper, we propose UniSage, a unified sampling framework that addresses this trade-off by adopting a post-analysis-aware paradigm. Unlike prior works that focus solely on tracing, UniSageintegrates both traces and logs, leveraging a lightweight anomaly detection and root cause analysis module to scan the full data stream before sampling decisions are made. This pre-computation enables a dual-pillar strategy: an analysis-guided sampler that retains high-value data associated with detected anomalies, and an edge-case sampler that preserves rare but critical behaviors to ensure diversity. Evaluation on three datasets confirms that UniSage achieves superior data retention. At a 2.5% sampling rate, UniSage captures 71% of critical traces and 96.25% of relevant logs, substantially exceeding the best existing methods (which achieve 42.9% and 1.95%, respectively). Moreover, evaluations on a real-world dataset demonstrate UniSage's efficiency; it processes a 20-minute multi-modal data block in an average of 10 seconds, making it practical for production environments.

cs.SE↗

arXiv2025

Potential of di-Higgs observation via a calibratable jet-free $HH\to 4b$ framework

We present a calibratable, jet-free framework that enhances the search significance of the flagship LHC channel $HH \to 4b$ by more than a factor of five compared to existing approaches. The method employs a mass-decorrelated discriminant to identify $h_1 h_2 \to 4b$ with variable $h_{1,2}$ masses and a simultaneous estimator of $(m_{h_1}, m_{h_2})$, both derived from multiclass classification on all-particle inputs. The $HH$ signal response can be calibrated using $ZZ \to 4b$. Using a highly realistic simulation framework validated through multiple tests, we demonstrate the method's robustness and identify two prerequisites essential for achieving this level of sensitivity. Results indicate that with LHC Run 2 and 3 data, observation-level sensitivity to $HH$ appears within reach, enabling constraints on $\kappa_\lambda$ comparable to HL-LHC projections and offering an accelerated path to precision measurements of the Higgs trilinear coupling.

hep-ph↗

arXiv2024

Raccoon: Prompt Extraction Benchmark of LLM-Integrated Applications

With the proliferation of LLM-integrated applications such as GPT-s, millions are deployed, offering valuable services through proprietary instruction prompts. These systems, however, are prone to prompt extraction attacks through meticulously designed queries. To help mitigate this problem, we introduce the Raccoon benchmark which comprehensively evaluates a model's susceptibility to prompt extraction attacks. Our novel evaluation method assesses models under both defenseless and defended scenarios, employing a dual approach to evaluate the effectiveness of existing defenses and the resilience of the models. The benchmark encompasses 14 categories of prompt extraction attacks, with additional compounded attacks that closely mimic the strategies of potential attackers, alongside a diverse collection of defense templates. This array is, to our knowledge, the most extensive compilation of prompt theft attacks and defense mechanisms to date. Our findings highlight universal susceptibility to prompt theft in the absence of defenses, with OpenAI models demonstrating notable resilience when protected. This paper aims to establish a more systematic benchmark for assessing LLM robustness against prompt extraction attacks, offering insights into their causes and potential countermeasures. Resources of Raccoon are publicly available at https://github.com/M0gician/RaccoonBench.

cs.CR↗

arXiv2024

Large-scale Outdoor Cell-free mMIMO Channel Measurement in an Urban Scenario at 3.5 GHz

The design of cell-free massive MIMO (CF-mMIMO) systems requires accurate, measurement-based channel models. This paper provides the first results from the by far most extensive outdoor measurement campaign for CF-mMIMO channels in an urban environment. We measured impulse responses between over 20,000 potential access point (AP) locations and 80 user equipments (UEs) at 3.5 GHz with 350 MHz bandwidth (BW). Measurements use a "virtual array" approach at the AP and a hybrid switched/virtual approach at the UE. This paper describes the sounder design, measurement environment, data processing, and sample results, particularly the evolution of the power-delay profiles (PDPs) as a function of the AP locations, and its relation to the propagation environment.

eess.SP↗