arXiv subjects

Yicong Chen

Publications and source records attributed to Yicong Chen.

8 recordsLinked to original sources

arXiv2026

Unified First-Principles Theory of Finite-Wave-Vector Photocurrents in Crystals

Spatially structured light carries independent phase and envelope variations in addition to its polarization and frequency. We develop a first-principles theory of second-order dc photocurrents (especially shift and injection) that resolves how these optical degrees of freedom drive distinct dc responses in crystals. The second-order dc response couples two optical field components at the same frequency but with generally different wave vectors. Expanding the response to first order in these wave vectors identifies two rank-four material tensors: $ξ$, which couples to the optical phase gradient and contains the plane-wave photon-drag limit, and $ζ$, which couples to the intensity gradient and describes a spatially varying dc current. Wannier-interpolated calculations for monolayer GeS show symmetry-allowed finite-wave-vector responses that survive at a centrosymmetric structure where conventional bulk photovoltaic effect vanishes. For a Gaussian beam with a uniform phase gradient, the phase-gradient contribution drives current in the same direction on both sides of the beam center, whereas the intensity-gradient contribution drives currents in opposite directions, showing that distinct photocurrent patterns can be selected through the wavefront and envelope of light. A multipolar analysis further resolves the optical corrections into electric-quadrupole, orbital magnetic-dipole, and band-dispersion contributions. Together, these results show how the spatial structure of light can serve as an independent control variable for nonlinear photocurrent generation and provide a first-principles route to predict this response in real materials.

cond-mat.mes-hall↗

arXiv2026

AVMeme Exam: A Multimodal Multilingual Multicultural Benchmark for LLMs' Contextual and Cultural Knowledge and Thinking

Internet audio-visual clips convey meaning through time-varying sound and motion, which extend beyond what text alone can represent. To examine whether AI models can understand such signals in human cultural contexts, we introduce AVMeme Exam, a human-curated benchmark of over one thousand iconic Internet sounds and videos spanning speech, songs, music, and sound effects. Each meme is paired with a unique Q&A assessing levels of understanding from surface content to context and emotion to usage and world knowledge, along with metadata such as original year, transcript, summary, and sensitivity. We systematically evaluate state-of-the-art multimodal large language models (MLLMs) alongside human participants using this benchmark. Our results reveal a consistent limitation: current models perform poorly on textless music and sound effects, and struggle to think in context and in culture compared to surface content. These findings highlight a key gap in human-aligned multimodal intelligence and call for models that can perceive contextually and culturally beyond the surface of what they hear and see. Project page: avmemeexam.github.io/public

cs.SD↗

arXiv2026

Spatially dispersive photogalvanic effects as a probe of quantum geometric tensor

Berry curvature and quantum metric of Bloch states govern a wide range of phenomena, yet unified experimental access to both remains limited. Here we show that light spatial-dispersion alters the selection rules of second-order photocurrents and responses forbidden by parity become allowed in centrosymmetric crystals without any external fields, magnetic order, interfaces, strain, or engineered symmetry breaking. The resulting response is intrinsic and its weight is set by the quantum geometry of the Bloch states. Conventional photogalvanic effects are constrained by crystal symmetry and entangle the quantum metric with shift vector contributions. The spatially-dispersive response instead isolates the quantum metric and Berry curvature in distinct polarization channels. Implementing this approach in 1T'-MoTe2 across its temperature-driven transition to Td-Weyl phase, we resolve helicity-even and helicity-odd photocurrents corresponding to quantum metric and Berry curvature contributions, respectively, from the same device. The metric-dominated response persists across both phases and exhibits a robust spectral structure reproduced by first-principles calculations and linked to momentum-resolved quantum metric hotspots. In contrast, the curvature-driven channel emerges only when inversion symmetry is broken and shows strong sensitivity to carrier doping through competing momentum-space contributions. Our results establish photogalvanic effects with spatially varying optical fields as a general route to accessing quantum geometry in materials where photon energy and electronic filling probe different parts of the excitation manifold.

cond-mat.mes-hall↗

arXiv2025

Baichuan-Omni-1.5 Technical Report

We introduce Baichuan-Omni-1.5, an omni-modal model that not only has omni-modal understanding capabilities but also provides end-to-end audio generation capabilities. To achieve fluent and high-quality interaction across modalities without compromising the capabilities of any modality, we prioritized optimizing three key aspects. First, we establish a comprehensive data cleaning and synthesis pipeline for multimodal data, obtaining about 500B high-quality data (text, audio, and vision). Second, an audio-tokenizer (Baichuan-Audio-Tokenizer) has been designed to capture both semantic and acoustic information from audio, enabling seamless integration and enhanced compatibility with MLLM. Lastly, we designed a multi-stage training strategy that progressively integrates multimodal alignment and multitask fine-tuning, ensuring effective synergy across all modalities. Baichuan-Omni-1.5 leads contemporary models (including GPT4o-mini and MiniCPM-o 2.6) in terms of comprehensive omni-modal capabilities. Notably, it achieves results comparable to leading models such as Qwen2-VL-72B across various multimodal medical benchmarks.

cs.CL↗

arXiv2024

Buffer-based Gradient Projection for Continual Federated Learning

Continual Federated Learning (CFL) is essential for enabling real-world applications where multiple decentralized clients adaptively learn from continuous data streams. A significant challenge in CFL is mitigating catastrophic forgetting, where models lose previously acquired knowledge when learning new information. Existing approaches often face difficulties due to the constraints of device storage capacities and the heterogeneous nature of data distributions among clients. While some CFL algorithms have addressed these challenges, they frequently rely on unrealistic assumptions about the availability of task boundaries (i.e., knowing when new tasks begin). To address these limitations, we introduce Fed-A-GEM, a federated adaptation of the A-GEM method (Chaudhry et al., 2019), which employs a buffer-based gradient projection approach. Fed-A-GEM alleviates catastrophic forgetting by leveraging local buffer samples and aggregated buffer gradients, thus preserving knowledge across multiple clients. Our method is combined with existing CFL techniques, enhancing their performance in the CFL context. Our experiments on standard benchmarks show consistent performance improvements across diverse scenarios. For example, in a task-incremental learning scenario using the CIFAR-100 dataset, our method can increase the accuracy by up to 27%. Our code is available at https://github.com/shenghongdai/Fed-A-GEM.

cs.LG↗

arXiv2024

Can MLLMs Perform Text-to-Image In-Context Learning?

The evolution from Large Language Models (LLMs) to Multimodal Large Language Models (MLLMs) has spurred research into extending In-Context Learning (ICL) to its multimodal counterpart. Existing such studies have primarily concentrated on image-to-text ICL. However, the Text-to-Image ICL (T2I-ICL), with its unique characteristics and potential applications, remains underexplored. To address this gap, we formally define the task of T2I-ICL and present CoBSAT, the first T2I-ICL benchmark dataset, encompassing ten tasks. Utilizing our dataset to benchmark six state-of-the-art MLLMs, we uncover considerable difficulties MLLMs encounter in solving T2I-ICL. We identify the primary challenges as the inherent complexity of multimodality and image generation, and show that strategies such as fine-tuning and Chain-of-Thought prompting help to mitigate these difficulties, leading to notable improvements in performance. Our code and dataset are available at https://github.com/UW-Madison-Lee-Lab/CoBSAT.

cs.LG↗

arXiv2024

Strong Chirality Suppression in 1-D correlated Weyl Semimetal (TaSe4)2I

The interaction of light with correlated Weyl semimetals (WSMs) provides a unique platform for exploring non-equilibrium phases and fundamental properties such as chirality. Here, we investigate the structural chirality of (TaSe4)2I, a correlated WSM, under weak optical pumping using Circular Photogalvanic Effect (CPGE) measurements and Raman spectroscopy. Surprisingly, we find that there is a loss of chirality in (TaSe4)2I above a threshold light intensity. We suggest that the loss of chirality is due to an optically driven phase transition into an achiral structure distinct from the ground state. This structural transformation is supported by fluence-dependent Raman spectra, revealing a new peak at low pump fluences that disappears above the threshold fluence. The loss of chirality even at low optical powers suggests that the system quickly transitions into a non WSM phase, and also highlights the importance of considering light-induced structural interactions in understanding the behavior of correlated systems. These studies showcase that even low excitation powers can be used to control the properties of correlated topological systems, opening up new avenues for low power optical devices.

cond-mat.mtrl-sci↗

arXiv2023

Opto-twistronic Hall effect in a three-dimensional spiral lattice

Studies of moire systems have elucidated the exquisite effect of quantum geometry on the electronic bands and their properties, leading to the discovery of new correlated phases. However, most experimental studies have been confined to a few layers in the 2D limit. The extension of twistronics to its 3D limit, where the twist is extended into the third dimension between adjacent layers, remains underexplored due to the challenges in precisely stacking layers. Here, we focus on 3D twistronics on a platform of self-assembled spiral superlattice of multilayered WS2. Our findings reveal an opto-twistronic Hall effect in the spiral superlattice. This mesoscopic response is an experimental manifestation of the noncommutative geometry that arises when translational symmetry is replaced by a non-symmorphic screw operation. We also discover signatures of altered laws of optical excitation, manifested as an unconventional photon momentum-lattice interaction owing to moire of moire modulations in the 3D twistronic system. Crucially, our findings mark the initial identification of higher-order quantum geometrical tensors in light-matter interactions. This breakthrough opens new avenues for designing quantum materials-based optical lattices with large nonlinearities, paving the way for the development of advanced quantum nanophotonic devices.

cond-mat.mes-hall↗