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Ting Sun

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Machine Learning Computation and Language cond-mat.mtrl-sci cond-mat.soft physics.ao-ph physics.optics physics.plasm-ph

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preprint2026arXiv

GameGen-Verifier: Parallel Keypoint-Based Verification for LLM-Generated Games via Runtime State Injection

LLM-based game generation promises to turn natural-language specifications into executable games, but progress is limited by the lack of reliable automated verification. Unlike conventional code generation, game correctness is defined over long-horizon interaction: a game may appear correct while violating core mechanics such as state updates, interaction rules, and phase transitions. Existing Agent-as-a-Verifier approaches collapse verification into open-ended gameplay, making verdicts reachability-bound, time-consuming, coverage-limited, and sensitive to the agent's gameplay ability. We present GameGen-Verifier, an automated verification paradigm for LLM-generated games that decomposes a specification into verifiable keypoints and grounds them into independent verification units. Each unit patches the game runtime into a concrete target state, executes a bounded interaction, and judges the outcome against the keypoint assertion. We implement GGV-Harness, a scalable agentic harness providing concurrency management, runtime isolation, and fault recovery. On VeriGame, our dataset of 100 games across seven genres, GameGen-Verifier achieves up to 92.2% accuracy against human judgments versus 58.8% for the coverage-enforced Agent-as-a-Verifier baseline, while reducing wall-clock time by up to 16.6x.

preprint2022arXiv

Production of polarized particle beams via ultraintense laser pulses

High-energy spin-polarized electron, positron, and $γ$-photon beams have many significant applications in the study of material properties, nuclear structure, particle physics, and high-energy astrophysics. Thus,efficient production of such polarized beams attracts a broad spectrum of research interests. This is driven mainly by the rapid advancements in ultrashort and ultraintense laser technology. Currently available laser pulses can achieve peak intensities in the range of $10^{22}-10^{23}$ Wcm$^{-2}$, with pulse durations of tens of femtoseconds. The dynamics of particles in laser fields of the available intensities is dominated by quantum electrodynamics (QED) and the interaction mechanisms have reached regimes spanned by nonlinear multiphoton absorbtion (strong-field QED processes). In strong-field QED processes, the scattering cross sections obviously depend on the spin and polarization of the particles, and the spin-dependent photon emission and the radiation-reaction effects can be utilized to produce the polarized particles. An ultraintense laser-driven polarized particle source possesses the advantages of high-brilliance and compactness, which could open the way for the unexplored aspects in a range of researches. In this work, we briefly review the seminal conclusions from the study of the polarization effects in strong-field QED processes, as well as the progress made by recent proposals for production of the polarized particles by laser-beam or laser-plasma interactions.

preprint2020arXiv

Application of Pre-training Models in Named Entity Recognition

Named Entity Recognition (NER) is a fundamental Natural Language Processing (NLP) task to extract entities from unstructured data. The previous methods for NER were based on machine learning or deep learning. Recently, pre-training models have significantly improved performance on multiple NLP tasks. In this paper, firstly, we introduce the architecture and pre-training tasks of four common pre-training models: BERT, ERNIE, ERNIE2.0-tiny, and RoBERTa. Then, we apply these pre-training models to a NER task by fine-tuning, and compare the effects of the different model architecture and pre-training tasks on the NER task. The experiment results showed that RoBERTa achieved state-of-the-art results on the MSRA-2006 dataset.

preprint2010arXiv

Assembling of three-dimensional crystals by large nonequilibrium depletion force

We propose and demonstrate a method to achieve large effective Soret coefficient in colloids by suitably mixing two different particles, e.g., silica beads and Fe3O4 nanoparticles. It is shown that the thermophoretic motion of Fe3O4 nanoparticles out of the heating region results in a large nonequlibrium depletion force for silica beads. Consequently, silica beads are driven quickly to the heating region, forming a three-dimensional crystal with few defects and dislocations. The binding of silica beads is so tight that a colloidal photonic crystal can be achieved after the complete evaporation of solvent, water. Thus, for fabrication of defect free colloidal PCs, periodic structures for molecular sieves, among others, the proposed technique could be a low cost alternative. In addition as we use biocompatible materials, this technique could be a tool for biophysics studies where the potential of large effective Soret coefficient could be useful.