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Chao Chen

Publications and source records attributed to Chao Chen.

At least 145 records · Page 8Linked to original sources
arXiv2026

GSAM: A Generalizable and Safe Robotic Framework for Articulated Object Manipulation

Articulated object manipulation is a unique challenge for service robots. Existing methods employ end-to-end policy learning, visionmotion planning, and large-language/visual-language model (LLM/VLM), but often overlook the diversity of articulated objects and the complexity of interactions between end-effector and handle, leading to limited generalization and destructive collisions. To address this, we propose GSAM, a generalizable and safe robotic framework for articulated object manipulation. Specifically, a vision-based perceiver generates the kinematic parameters. Considering that pre-trained markers in perceiver yield raw estimations that may deviate from commonsense, we present a f ine-tuned VLM-based refiner, using chain-of-thought (COT) commonsense reasoning to refine perception. To prevent destructive collisions, we design an interaction constraint function generator, integrating articulated object, interaction pose, and obstacle avoidance knowledge into a base. LLM then functionalize these constraints and apply them to trajectory and posture planning. A kinematic-aware manipulation planner verifies reachability for trajectory and posture. Experiments on 50 hinge tasks across 5 object categories and 50 randomly initialized end-effectorhandle configurations show that GSAM reduces standard deviation by 3.1% and improves manipulation success rate by 36.0% compared to the best baseline, respectively demonstrating the superior object generalization and interaction safety of GSAM in practical scenarios.

cs.RO↗
arXiv2026

Learning Bijective Surface Parameterization for Inferring Signed Distance Functions from Sparse Point Clouds with Grid Deformation

Inferring signed distance functions (SDFs) from sparse point clouds remains a challenge in surface reconstruction. The key lies in the lack of detailed geometric information in sparse point clouds, which is essential for learning a continuous field. To resolve this issue, we present a novel approach that learns a dynamic deformation network to predict SDFs in an end-to-end manner. To parameterize a continuous surface from sparse points, we propose a bijective surface parameterization (BSP) that learns the global shape from local patches. Specifically, we construct a bijective mapping for sparse points from the parametric domain to 3D local patches, integrating patches into the global surface. Meanwhile, we introduce grid deformation optimization (GDO) into the surface approximation to optimize the deformation of grid points and further refine the parametric surfaces. Experimental results on synthetic and real scanned datasets demonstrate that our method significantly outperforms the current state-of-the-art methods. Project page: https://takeshie.github.io/Bijective-SDF

cs.CV↗
arXiv2026

Rethinking Federated Unlearning via the Lens of Memorization

Federated learning (FL) increasingly needs machine unlearning to comply with privacy regulations. However, existing federated unlearning approaches may overlook the overlapping information between the unlearning and remaining data, leading to ineffective unlearning and unfairness between clients. In this work, we revisit federated unlearning through the lens of memorization. We argue that unlearning should mainly remove the unique memorized information attributable to the data to be forgotten, while preserving overlapping patterns that are also supported by the remaining data. Specifically, we propose Grouped Memorization Evaluation, an example-level metric that separates memorized knowledge from overlapping knowledge. Building on this metric, we introduce Federated Memorization Pruning (FedMemPrune), a pruning-based unlearning approach that resets redundant parameters responsible for memorization. Extensive experiments show that FedMemPrune closely matches retraining-based unlearning baselines while more effectively eliminating memorization than existing federated unlearning algorithms, yielding strong unlearning performance without sacrificing the utility of retained knowledge.

cs.LG↗
arXiv2026

Study of the reactions $\bar{n} p \to 2π^{+}π^{-}$, $2π^{+}π^{-}π^{0}$, and $2π^{+}π^{-}2π^{0}$ using $J/ψ\to p π^{-}\bar{n}$

We report an experimental investigation of the reactions $\bar{n} p \to 2π^{+}π^{-}$, $\bar{n} p \to 2π^{+}π^{-}π^{0}$, and $\bar{n} p \to 2π^{+}π^{-}2π^{0}$ using $(10.087 \pm 0.044) \times 10^{9}$ $J/ψ$ events collected with the BESIII detector at the BEPCII storage ring. The antineutron ($\bar{n}$) is produced in the decay $J/ψ\to p π^{-} \bar{n}$ with studied momentum from 200~MeV/$c$ to 1174~MeV/$c$, while the target proton originates from the hydrogen nuclei in the cooling oil of the beam pipe. This novel method pioneers the study of $\bar{n}$-nucleon interactions at an $e^{+}e^{-}$ collider, providing the first experimental data for $\bar{n}$ momenta exceeding 800~MeV/$c$.

hep-ex↗
arXiv2026

TransitLM: A Large-Scale Dataset and Benchmark for Map-Free Transit Route Generation

Public transit route planning traditionally depends on structured map infrastructure and complex routing engines, and no existing dataset supports training models to bypass this dependency. We present TransitLM, a large-scale dataset of over 13 million transit route planning records from four Chinese cities covering 120,845 stations and 13,666 lines, released as a continual pre-training corpus and benchmark data for three evaluation tasks with complementary metrics. Experiments show that an LLM trained on TransitLM produces structurally valid routes at high accuracy and implicitly grounds arbitrary GPS coordinates to appropriate stations without any explicit mapping. These results demonstrate that transit route planning can be learned entirely from data, enabling end-to-end, map-free route generation directly from origin-destination information. The dataset and benchmark are available at https://huggingface.co/datasets/GD-ML/TransitLM, with evaluation code at https://github.com/HotTricker/TransitLM.

cs.CL↗
arXiv2026

Measurement of Born Cross Sections for $e^+e^- \to K^+Ξ^0\barΣ^-$ at $\sqrt{s} = 3.51-4.95$ GeV and Observation of $ψ(3770) \to K^+Ξ^0\barΣ^-$

Using 44.55 fb$^{-1}$ of $e^+e^-$ collision data collected by the BESIII detector at the BEPCII collider, we report the first measurement of the Born cross sections for the $e^+e^- \to K^+Ξ^0\barΣ^-$ reaction at fifty-six center-of-mass energies between 3.51 and 4.95~GeV. A fit to the dressed cross sections reveals the first observation of the $ψ(3770) \to K^+Ξ^0\barΣ^-$ process, with a statistical significance of 6.0$σ$ including systematic uncertainties. This result represents the first observation of charmless three-body baryonic decay of a vector charmonium state above the open-charm threshold. No significant signals for other charmonium(-like) states i.e., $ψ(4040)$, $ψ(4160)$, $Y(4230)$, $Y(4360)$, $ψ(4415)$, $Y(4500)$, $Y(4660)$ or $Y(4710)$ are observed, and the upper limits for the product of the branching fraction and the electronic partial width at the 90% confidence level for each assumed charmonium(-like) state are provided. Additionally, the ratios of Born cross sections between this work and the previous measurements of $e^+e^- \to K^{0}_{S}\barΞ^{-}Σ^-$ and $K^-\barΞ^+\barΣ^0$ are provided, which can be used to validate theoretical predictions related to isospin symmetry.

hep-ex↗
arXiv2026

Precise Measurement of Matter-Antimatter Asymmetry with Entangled Hyperon Antihyperon Pairs

A search for $CP$ violation with an entangled system of $Ξ^-\barΞ^+$ pairs is performed, using $(10,087\pm44)\times10^{6}$ $J/ψ$ events collected with the BESIII experiment. A nine-dimensional helicity amplitude is used to fit $e^+e^- \to J/ψ\toΞ^-\barΞ^+$ and its subsequent decays. The $Ξ^-$ and $Ξ^+$ decay parameters are determined with higher precision compared to the best results reported so far. Furthermore, the strong phase difference, $(δ_P-δ_S)=(0.3\pm1.2\pm0.2)\times10^{-2}~\text{rad}$, and the weak phase difference, $(ξ_P-ξ_S)=(-0.2\pm1.2\pm0.1)\times10^{-2}~\text{rad}$, are directly determined. These are the most precise measurements to date. The $CP$ asymmetry observables $A_{CP}^Ξ=(-7.8\pm4.8\pm0.8)\times10^{-3}$ and $Δϕ_{CP}^Ξ=(0.6\pm5.1\pm0.2)\times10^{-3}~\text{rad}$ are determined, which are consistent with $CP$ conservation. In addition, independent measurements of the $Λ$ decay parameter and $CP$ asymmetry $A^Λ_{CP}=(-2.9\pm4.3\pm0.7)\times10^{-3}$ are also obtained, which are in agreement with the previous measurements, but with much improved precision.

hep-ex↗
arXiv2026

Search for the charmonium semi-leptonic weak decay $J/ψ\rightarrow D_s^-e^+ν_e+c.c.$

Using a data sample of $(10087 \pm 44) \times 10^6$ $J/ψ$ events collected with the BESIII detector at a centre-of-mass energy of $\sqrt{s}=3.097\ \textrm{GeV}$, a dedicated search for the charmonium semileptonic weak decay $J/ψ\rightarrow D_s^-e^+ν_e + \text{c.c.}$ is performed. No significant signal is observed. An upper limit on the branching fraction is set at $\mathcal{B}(J/ψ\rightarrow D_s^- e^+ ν_e + \text{c.c.}) < 9.9 \times 10^{-8}$ at the 90\% confidence level. This result improves upon previous constraints by an order of magnitude, representing the most stringent experimental limit to date. It thus provides a critical test of Standard Model predictions and new physics scenarios in heavy-quark dynamics.

hep-ex↗
arXiv2026

EnvFactory: Scaling Tool-Use Agents via Executable Environments Synthesis and Robust RL

Equipping LLMs with tool-use capabilities via Agentic Reinforcement Learning (Agentic RL) is bottlenecked by two challenges: the lack of scalable, robust execution environments and the scarcity of realistic training data that captures implicit human reasoning. Existing approaches depend on costly real-world APIs, hallucination-prone LLM simulators, or synthetic environments that are often single-turn or depend on pre-collected documents. Moreover, synthetic trajectories are frequently over-specified, resembling instruction sequences rather than natural human intents, reducing their effectiveness for RL training. We introduce EnvFactory, a fully automated framework that addresses both challenges. EnvFactory autonomously explores and verifies stateful, executable tool environments from authentic resources, and synthesizes natural multi-turn trajectories through topology-aware sampling and calibrated refinement, producing grounded queries with implicit intents. Using only 85 verified environments across 7 domains, EnvFactory generates 2,575 SFT and RL trajectories. Despite using significantly fewer environments than prior work, which are often 5 times more, EnvFactory achieves superior training efficiency and downstream performance, improving Qwen3-series models by up to +15% on BFCLv3, +8.6% on MCP-Atlas, and +6% on conversational benchmarks including $τ^2$-Bench and VitaBench. By fully automating both environment construction and trajectory synthesis, EnvFactory provides a scalable, extensible, and robust foundation for Agentic RL.

cs.CL↗
arXiv2026

Observation of $η_c(1S)\to Σ^0\bar Σ^0$ and search for $h_c(1P)\to Σ^0\bar Σ^0$ via $ψ(3686)$ transitions

Using $(2712.4 \pm 14.3) \times 10^6~ψ(3686)$ events collected by the BESIII detector operating at the BEPCII collider, the hadronic decay $η_{c}\toΣ^{0}\bar{Σ^{0}}$ is observed for the first time via the radiative transition from $ψ(3686)$. It is found that the branching fraction has a significant dependence on the interference pattern between $η_c(1S)$ and non-$η_c(1S)$ processes. They are determined to be $\displaystyle\mathcal{B}(η_c(1S) \to Σ^{0}\bar{Σ^{0}}) = (2.59 \pm 0.14(stat) \pm 0.44(syst)) \times 10^{-3}$ and $(1.18 \pm 0.12(stat) \pm 0.21(syst)) \times 10^{-3}$, for the destructive and constructive interference scenarios, respectively. No significant signal is observed for the decay $h_{c}\toΣ^{0}\bar{Σ^{0}}$ in the hadronic transition $ψ(3686)\toπ^0h_{c}$, and an upper limit on its branching fraction is set to be $1.02\times 10^{-4}$ at the 90\% confidence level.

hep-ex↗
arXiv2026

Search for the charmonium weak decay $J/ψ\to\bar{D}^0\bar{K}^{*0}+{\rm c.c.}$

Based on a sample of $(10087\pm44)\times10^6$ $J/ψ$ events collected at the center-of-mass energy $\sqrt{s}$ = 3.0969 GeV with the BESIII detector, we search for the charmonium rare weak decay $J/ψ\to\bar{D}^0\bar{K}^{*0}+{\rm c.c.}$. No significant signal is observed, and the upper limit on its decay branching fraction at the 90% confidence level is set as $1.4\times10^{-7}$, improving the sensitivity of the previous best limit by an order of magnitude.

hep-ex↗
arXiv2026

Cross Section Measurements of $\bar{n}p \rightarrow K^{+}K^{-}π^{+}(π^{0})$ via Antineutrons Produced by $J/ψ\to p π^{-} \bar{n}$ Decays

Based on a novel method for producing antineutrons via $J/ψ$ decays, we report a study of $\bar{n}p$ inelastic scattering into final states containing kaons. The analysis uses $(10087\pm44)\times 10^6$ $J/ψ$ events collected at the BESIII detector operating at the BEPCII storage ring. Antineutrons are produced via $J/ψ\to p π^{-} \bar{n}$ decays and tagged by the detected protons and pions, resulting in antineutron momenta ranging from 0 to 1174~MeV/$c$, while target protons are provided by the hydrogen in the beam-pipe material. The flux-averaged cross sections of the reactions $\bar{n}p \rightarrow K^{+}K^{-}π^{+}$ and $\bar{n}p \rightarrow K^{+}K^{-}π^{+}π^{0}$ over this antineutron momentum spectrum are measured to be $0.53^{+0.15}_{-0.12} \pm 0.08$~mb and $1.09^{+0.36}_{-0.30} \pm 0.31$~mb, respectively, where the first uncertainties are statistical and the second are systematic. Due to limited statistics, the intermediate states in these processes are not quantitatively investigated. The observation of clean antineutron-proton scattering candidates indicates the potential of this approach for future investigations of antineutron-proton interactions.

hep-ex↗
arXiv2026

Topo-R1: Detecting Topological Anomalies via Vision-Language Models

Topology is critical in tubular structures such as blood vessels, nerve fibers, and road networks, where connectivity and loop structure govern downstream functional analysis. Vision-Language Models (VLMs) are promising candidates for understanding such structures, given their reasoning and grounding capabilities. To probe their topological perception, we systematically evaluate leading closed- and open-source VLMs on localizing and classifying four canonical topological anomalies (broken/spurious connections, missing/extra branches) in tubular-network segmentation masks. They perform nearly at random, indicating that topology-aware perception is largely absent from current general-purpose VLMs. As no existing resource pairs segmentation masks with localized anomaly annotations, we build an automated, multi-domain data-curation pipeline that synthesizes diverse topological perturbations with verifiable Betti-number annotations across graduated difficulty levels, yielding the first systematic benchmark with a large-scale training set and held-out in-distribution (ID) and out-of-distribution (OOD) test suites. Building on this benchmark, we introduce Topo-R1, centered on a topology-aware composite reward that jointly scores localization, classification, and skeleton-level structural fidelity. Supervised fine-tuning cold-starts schema-compliant outputs, and Group Relative Policy Optimization (GRPO) then optimizes the policy against this reward, steering predictions toward topologically meaningful structure rather than superficial pixel overlap. Extensive experiments show that Topo-R1 substantially outperforms general-purpose VLMs and matches or exceeds supervised baselines across ID, OOD, and real-segmentation-output protocols, establishing a strong foundation for VLM-based topological understanding of structured visual data.

cs.CV↗
arXiv2026

Study of $ϕ\to K\bar{K}$ in the amplitude analysis of $D^{+}\to K_{S}^{0}K_{L}^{0}π^{+}$

We present the first amplitude analysis and branching fraction measurement of $D^{+} \rightarrow K_{S}^{0}K_{L}^{0}π^{+}$ decay. The analysis uses a dataset corresponding to an integrated luminosity of 20.3~$\rm fb^{-1}$, which was recorded at a center-of-mass energy 3.773~GeV by the BESIII detector. The measured branching fraction is $\mathcal{B}(D^{+} \rightarrow K_{S}^{0}K_{L}^{0}π^{+})=(5.780\pm0.085\pm 0.052)\times10^{-3}$, where the first uncertainty is statistical and the second is systematic. Using the known value of ${\cal B}(D^+ \to ϕπ^+,\,ϕ\to K^+K^-)$, we determine the relative branching fraction between $ϕ\to K_{S}^0K_{L}^0$ and $ϕ\to K^+K^-$ to be $\mathcal{B}(D^{+} \to ϕπ^{+}, ϕ\to K_{S}^0K_{L}^0)/\mathcal{B}(D^{+} \to ϕπ^{+}, ϕ\to K^+K^-)= 0.628\pm0.022\pm 0.015\pm0.017$, where the third uncertainty is related to $\mathcal{B}(D^{+} \to ϕπ^{+}, ϕ\to K^+K^-)$. This result is significantly lower than the previous world average and is consistent with the isospin expectation for the $ϕ$ meson's coupling to charged and neutral kaon pairs.

hep-ex↗
arXiv2026

ORCE: Order-Aware Alignment of Verbalized Confidence in Large Language Models

Large language models (LLMs) often produce answers with high certainty even when they are incorrect, making reliable confidence estimation essential for deployment in real-world scenarios. Verbalized confidence, where models explicitly state their confidence in natural language, provides a flexible and user-facing uncertainty signal that can be applied even when token logits are unavailable. However, existing verbalized-confidence methods often optimize answer generation and confidence generation jointly, which can cause confidence-alignment objectives to interfere with answer accuracy. In this work, we propose a decoupled and order-aware framework for verbalized confidence calibration. Our method first generates an answer and then estimates confidence conditioned on the fixed question--answer pair, allowing confidence optimization without directly perturbing the answer-generation process. To align confidence with correctness likelihood, we construct a sampling-based surrogate from multiple model completions and optimize rank-based reinforcement learning objectives that encourage responses with higher estimated correctness likelihood to receive higher verbalized confidence. Experiments on reasoning and knowledge-intensive benchmarks show that our method improves calibration and failure prediction performance while largely preserving answer accuracy. These results demonstrate that verbalized confidence can be more reliably aligned by decoupling confidence estimation from answer generation and optimizing the relative ordering of confidence across responses.

cs.LG↗
arXiv2026

Amplitude Analysis and Branching Fraction Measurement of $D^+ \to π^+π^0π^0$

We present the first amplitude analysis of the hadronic decay $D^+\toπ^+π^0π^0$, using $e^{+}e^{-}$ collision data collected with the BESIII detector at a center-of-mass energy of 3.773~GeV, corresponding to an integrated luminosity of 20.3~fb$^{-1}$. The fit fractions of the intermediate processes are measured, in which the $D^+ \to ρ(770)^+π^0$ component is found to be dominant with a branching fraction of $(3.08\kern0.15em\pm\kern0.15em0.10_{\rm stat.}\pm0.05_{\rm syst.})\times10^{-3}$. Based on the amplitude analysis, the branching fraction of $D^+ \to π^+π^0π^0$ is measured to be $(4.84\kern0.1em\pm\kern0.1em0.05_{\rm stat.}\kern0.1em\pm\kern0.1em0.05_{\rm syst.})\times10^{-3}$. In addition, the CP asymmetries, both for specific amplitudes and integrated over the entire phase space, are measured.

hep-ex↗
arXiv2026

Soft and Hard Scaled Relative Graphs for Nonlinear Feedback Stability

This article presents input-output stability analysis of nonlinear feedback systems based on the notion of soft and hard scaled relative graphs (SRGs). The soft and hard SRGs acknowledge the distinction between incremental positivity and incremental passivity and reconcile them from a graphical perspective. The essence of our proposed analysis is that the separation of soft SRGs or hard SRGs of two open-loop systems on the complex plane guarantees closed-loop stability. The main results generalize an existing soft SRG separation theorem for bounded open-loop systems which was proved based on interconnection properties of soft SRGs under a chordal assumption. By comparison, our analysis does not require this chordal assumption and applies to possibly unbounded open-loop systems based on their hard SRGs.

eess.SY↗
arXiv2026

Ward Identity Constraints on Loop Corrections in Non-Attractor Inflation

The conservation of super-horizon curvature perturbations in strongly interacting inflationary models, particularly in the presence of quantum-loop corrections, remains a topic of active debate. We found that this conservation is essentially a direct consequence of the symmetry in perturbation theory. We demonstrate that the associated Ward identity imposes strict non-perturbative constraints on the infrared power spectrum. This finding provides a rigorous, symmetry-based framework for understanding nonlinear quantum fluctuations in the primordial universe.

astro-ph.CO↗