arXiv subjects

Bill Chen

Publications and source records attributed to Bill Chen.

4 recordsLinked to original sources

arXiv2026

Adaptive Solitons

Femtosecond laser pulses have incredible potential but still face some performance and stability issues. Here we discover a new nonlinear optical effect, frequency-comb-induced stimulated Brillouin scattering resonance, which can only be excited by a new type of soliton, adaptive solitons. Adaptive solitons possess the unique properties of adaptive down-chirp which breaks area theorem limitation on pulse energy in normal dispersion lasers, spectral profile self-regulation which provides high pulse contrast and breaks gain narrowing limitation in amplifiers, and freedom from dispersive radiation that weakens and deforms current ultrashort laser pulses in transmission media. More intriguingly, they have an adaptive transmission gain in normal dispersion waveguides which has the potential to enable them to be lossless in long normal dispersion waveguides for repeaterless soliton communication. A passive frequency-modulation mode-locked fiber laser was successfully built and generated incredibly stable adaptive solitons. Even though the laser had no negative dispersion elements, the output solitons were measured as down-chirped which enables them to keep soliton properties in normal dispersion waveguides, perfect for ultrafast applications with waveguide delivery. With the advantages of high consistency, high pulse contrast, and high energy capability; adaptive solitons are excellent for fields including micromachining, laser surgery, quantum computing, and spectroscopy.

physics.optics↗

arXiv2026

OpenAI GPT-5 System Card

This is the system card published alongside the OpenAI GPT-5 launch, August 2025. GPT-5 is a unified system with a smart and fast model that answers most questions, a deeper reasoning model for harder problems, and a real-time router that quickly decides which model to use based on conversation type, complexity, tool needs, and explicit intent (for example, if you say 'think hard about this' in the prompt). The router is continuously trained on real signals, including when users switch models, preference rates for responses, and measured correctness, improving over time. Once usage limits are reached, a mini version of each model handles remaining queries. This system card focuses primarily on gpt-5-thinking and gpt-5-main, while evaluations for other models are available in the appendix. The GPT-5 system not only outperforms previous models on benchmarks and answers questions more quickly, but -- more importantly -- is more useful for real-world queries. We've made significant advances in reducing hallucinations, improving instruction following, and minimizing sycophancy, and have leveled up GPT-5's performance in three of ChatGPT's most common uses: writing, coding, and health. All of the GPT-5 models additionally feature safe-completions, our latest approach to safety training to prevent disallowed content. Similarly to ChatGPT agent, we have decided to treat gpt-5-thinking as High capability in the Biological and Chemical domain under our Preparedness Framework, activating the associated safeguards. While we do not have definitive evidence that this model could meaningfully help a novice to create severe biological harm -- our defined threshold for High capability -- we have chosen to take a precautionary approach.

cs.CL↗

arXiv2025

Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025

The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025, at the University of California, Berkeley, in Berkeley, California, USA. As part of this year's program, we hosted Research Roundtables to catalyze collaborative, small-group dialogue around critical, timely topics at the intersection of machine learning and healthcare. Each roundtable was moderated by a team of senior and junior chairs who fostered open exchange, intellectual curiosity, and inclusive engagement. The sessions emphasized rigorous discussion of key challenges, exploration of emerging opportunities, and collective ideation toward actionable directions in the field. In total, eight roundtables were held by 19 roundtable chairs on topics of "Explainability, Interpretability, and Transparency," "Uncertainty, Bias, and Fairness," "Causality," "Domain Adaptation," "Foundation Models," "Learning from Small Medical Data," "Multimodal Methods," and "Scalable, Translational Healthcare Solutions."

cs.LG↗

arXiv2024

Building an Open-Source Community to Enhance Autonomic Nervous System Signal Analysis: DBDP-Autonomic

Smartphones and wearable sensors offer an unprecedented ability to collect peripheral psychophysiological signals across diverse timescales, settings, populations, and modalities. However, open-source software development has yet to keep pace with rapid advancements in hardware technology and availability, creating an analytical barrier that limits the scientific usefulness of acquired data. We propose a community-driven, open-source peripheral psychophysiological signal pre-processing and analysis software framework that could advance biobehavioral health by enabling more robust, transparent, and reproducible inferences involving autonomic nervous system data.

cs.HC↗