arXiv subjects

Yujian Chen

Publications and source records attributed to Yujian Chen.

6 recordsLinked to original sources

arXiv2026

The Generative Gap Between Speculative Drafter and Continuous Diffusion Language Model

Continuous diffusion language models (CDLMs) and speculative drafters offer efficient language generation but are typically evaluated differently: CDLMs generate independently through iterative refinement, whereas drafters propose text for target-model verification and correction. We compare their architectures without verification, using LangFlow for CDLMs and adapting DSpark's Markov and recurrent-head architectures for standalone generation. All models are trained from scratch for unconditional, single-block OpenWebText generation at lengths 16, 128, and 1024, without target features or verification, using common preprocessing, backbone dimensions, and training-update budgets. We evaluate generation perplexity (GenPPL) with an external language model and distributional similarity to reference text with MAUVE. With default denoising steps equal to sequence length, LangFlow outperforms both DSpark variants on both metrics at lengths 128 and 1024, while DSpark-RNN leads at 16. A conditional KL analysis characterizes dependencies excluded by the Markov head's previous-token conditioning. Recurrent memory removes this restriction and improves both metrics, but the longer-sequence gap persists. Teacher probability matching further lowers Markov GenPPL without observed MAUVE gains. Increasing LangFlow's denoising steps at fixed weights improves both metrics at lengths 16 and 128, changing the length-128 ordering relative to DSpark-RNN. These results establish LangFlow's longer-sequence advantage under the evaluated budgets and highlight iterative full-sequence refinement as a route to improving standalone generation beyond gains from recurrent head memory.

cs.CL↗

arXiv2026

Designing Transformers for Continuous Diffusion Language Models

Continuous diffusion language models (CDLMs) offer an alternative approach to parallel language generation; however, most existing studies directly use transformer architectures from either causal large language models (LLMs) or Diffusion Transformers (DiTs) for image generation, which were not optimized for CDLMs. In this paper, we conduct a systematic study on Transformer architectures for CDLMs and introduce Language Diffusion Transformer (LangDiT), combining feature and query-key normalization, wider noise conditioning, likelihood-shortcut gradient routing and calibration, and confidence-gated training self-conditioning. LangDiT significantly reduces generation perplexity in matched LangFlow comparisons, establishing a new state of the art in continuous language generation across different model formulations. Using LangFlow as a representative CDLM, LangDiT as a plug-and-play backbone leads to a new state-of-the-art model with a generation perplexity (GenPPL) of 21.72 using 1024 NFEs and 44.72 GenPPL using 128 NFEs on the unconditional generation of 1024-token sequences on the OpenWebText dataset. When adapted to Plaid-style CDLM formulations, LangDiT results in a new leading GenPPL of 11.33 using 1024 denoising NFEs, and 27.51 GenPPL using 128 denoising NFEs. These gains are achieved while retaining each model's underlying representation, training objective, and inference sampler, isolating transformer architecture as a fundamental source of improvement. Our study identifies architectural design as an important source of improvement in continuous diffusion language models.

cs.AI↗

arXiv2026

A 20-kV Optical-Injection-Enhanced 4H-SiC Reverse-Conducting IGBT With Snapback-Free Operation and Low On-State Voltage

This letter proposes a 20-kV 4H-SiC optical-injection-enhanced reverse-conducting IGBT (OIE-RC-IGBT) with snapback-free operation and low on-state voltage. Light-emitting diodes (LEDs) are integrated into the gate structure to provide optical injection during forward conduction. The emitted light generates a high concentration of photogenerated carriers in the carrier-storage layer (CSL) and drift region, thereby reducing the resistance of the JFET and drift regions and increasing the device current. Consequently, the collector-side P+/N junction is turned on earlier, effectively suppressing the snapback effect and facilitating the transition to bipolar conduction. After bipolar conduction is established, the photogenerated carriers further enhance conductivity modulation, resulting in a reduced on-state voltage. TCAD simulation results show that, compared with the conventional RC-IGBT (C-RC-IGBT), the proposed device achieves snapback-free operation while reducing the required number of MOS cells from 25 to 5. Moreover, the on-state voltage, turn-off fall time, and turn-off energy loss are reduced by 22.37%, 25.06%, and 19.69%, respectively. These results demonstrate the potential of optical injection for improving the conduction and turn-off performance of ultrahigh-voltage SiC RC-IGBTs.

physics.app-ph↗

arXiv2026

Goodness-of-fit and utility estimation: what's possible and what's not

A goodness-of-fit index measures the consistency of consumption data with a given model of utility-maximization. We show that for the class of well-behaved (i.e., continuous and increasing) utility functions there is no goodness-of-fit index that is continuous and accurate, where the latter means that a perfect score is obtained if and only if a dataset can be rationalized by a well-behaved utility function. While many standard goodness-of-fit indices are inaccurate we show that these indices are (in a sense we make precise) essentially accurate. Goodness-of-fit indices are typically generated by loss functions and we find that standard loss functions usually do not yield a best-fitting utility function when they are minimized. Nonetheless, welfare comparisons can be made by working out a robust preference relation from the data.

econ.TH↗

arXiv2024

Prolonging Carrier Lifetime in P-type 4H-SiC Epilayer by Thermal Oxidation and Hydrogen Annealing

A minority carrier lifetime of 25.46 $μ$s in a P-type 4H-SiC epilayer has been attained through sequential thermal oxidation and hydrogen annealing. Thermal oxidation can enhance the minority carrier lifetime in the 4H-SiC epilayer by reducing carbon vacancies. However, this process also generates carbon clusters with limited diffusivity and contributes to the enlargement of surface pits on the 4H-SiC. High-temperature hydrogen annealing effectively reduces stacking fault and dislocation density. Moreover, electron spin resonance analysis indicates a significant reduction in carbon vacancy defects after hydrogen annealing. The mechanisms of the elimination of carbon vacancies by hydrogen annealing include the decomposition of carbon clusters formed during thermal oxidation and the low-pressure selective etching by hydrogen, which increases the carbon content on the 4H-SiC surface and facilitates carbon diffusion. Consequently, the combination of thermal oxidation and hydrogen annealing eliminates carbon vacancies more effectively, substantially enhancing the minority carrier lifetime in P-type 4H-SiC. This improvement is advantageous for the application of high-voltage SiC bipolar devices.

cond-mat.mtrl-sci↗

arXiv2024

A Light-Emitting-Diodes-Integrated Silicon Carbide Insulated Gate Bipolar Transistor

A light-emitting-diodes (LEDs)-integrated silicon carbide (SiC) insulated gate bipolar transistors (LI-IGBT) is proposed in this paper. The novelty of the LI-IGBT depends on the photogeneration effect of III-nitride LEDs embedded in the poly-Si regions of IGBT. Then, the photogenerated carriers are formed in the JFET region and the drift layer, indicating the increase of the conductivity in LI-IGBT as compared with the SiC IGBT with hole-barrier layer (H-IGBT) and the SiC IGBT with charge storage layer (CSL-IGBT). The static simulation results show that the electron density of the LI-IGBT at the middle of the drift layer is separately 17.44 times and 15.81 times higher than those of the H-IGBT and CSL-IGBT, yielding 40.91% and 37.38% reduction of forward voltage drop, respectively, and also, the LI-IGBT shows 304.59% and 263.67% improvements in BFOM as compared with CSL-IGBT and H-IGBT, respectively. For the dynamic simulation in one cycle, the loss of LI-IGBT is separately reduced by 6.57% and 8.57% compared to H-IGBT and CSL-IGBT. Meanwhile, the relationship between VC(sat) and Eturn-off can be optimized by adjusting collector doping and minority carrier lifetime. These results reveal that the proposed SiC IGBT will be more suitable for ultra-high voltage application.

physics.app-ph↗