arXiv subjects

Zheng Qi

Publications and source records attributed to Zheng Qi.

At least 19 recordsLinked to original sources

arXiv2026

Self-Synchronized Terahertz and X-Ray Free-Electron Lasers from a Single Pre-Bunched Electron Beam

Ultrafast pump-probe spectroscopy combining intense terahertz (THz) and X-ray pulses is a critical tool for investigating complex structural and electronic dynamics in materials. However, current setups combining THz sources and X-ray free-electron lasers (FELs) often suffer from high system complexity, inherent timing jitter, or limited THz pulse properties. Here, we experimentally demonstrate the generation of intrinsically synchronized, strong-field, narrow-band THz and X-ray FELs from a single pre-bunched electron beam. Sequentially passing the beam through X-ray and THz amplifiers reveals a highly synergistic process: the initial periodic THz density modulation notably boosts the X-ray FEL pulse energy, while robustly surviving the intense X-ray emission to drive high-power, narrow-band THz radiation. Originating from the same electron bunch, the two pulses inherently maintain a precise, constant time delay. This jitter-free scheme establishes a highly reliable platform tailored for both X-ray-pump/THz-probe and THz-pump/X-ray-probe experiments.

physics.acc-ph↗

arXiv2026

Memory Layer: Train the In-Model Cache for Recommendation Models

Early ranking stages in recommendation systems precompute item embeddings and cache them in-model for scoring within strict latency constraints. Because this cache exists only at serving time, outside the training loop, training and serving use different item representations, a structural discrepancy that limits quality and adds operational fragility. We show that co-designing the training and serving paths removes this representation discrepancy at its source. We introduce the memory layer, an in-model key-value embedding cache co-trained with the model: the item tower writes embeddings during training and the model reads them at serving, one source of truth for item representations by construction. Always-on embeddings cover items not yet cached, so every item receives a prediction, and the design consolidates three separate trainer-to-predictor update paths into a single self-contained pipeline. Deployed in production on Instagram Reels, the memory layer raises prediction coverage from 96% to 100%, improves embedding freshness from $O(5\text{ min})$ to $O(20\text{ s})$, and narrows the training-serving Normalized Entropy (NE) gap by up to 86%, yielding over $2\times$ recall for the freshest content and a 5-6% cold start engagement lift. Because embeddings are produced during training, the system needs no separate bulk-evaluation or publish-time recomputation, cutting training-and-publish computational cost by 30% at neutral serving computational cost.

cs.IR↗

arXiv2026

Capturing Gaze Shifts for Guidance: Cross-Modal Fusion Enhancement for VLM Hallucination Mitigation

Vision language models (VLMs) often generate hallucination, i.e., content that cannot be substantiated by either textual or visual inputs. Prior work primarily attributes this to over-reliance on linguistic prior knowledge rather than visual inputs. Some methods attempt to mitigate hallucination by amplifying visual token attention proportionally to their attention scores. However, these methods overlook the visual attention sink problem, where attention is frequently misallocated to task-irrelevant visual regions, and neglect cross-modal fusion balance by enhancing only visual attention without adjusting attention to the user query. This can result in amplifying incorrect areas while failing to properly interpret the user query. To address these challenges, we propose a simple yet effective method called Gaze Shift-Guided Cross-modal Fusion Enhancement (GIFT). GIFT pre-computes a holistic visual saliency map by tracking positive changes in visual attention, or "gaze shifts", during user query comprehension, and leverages this map to amplify attention to both salient visual information and the user query at each decoding step. This reduces the impact of visual attention sink, as irrelevant tokens exhibit minimal shifts, while ensuring balanced cross-modal fusion for well-integrated representation. Extensive experiments show that GIFT effectively mitigates hallucination in VLMs across both generative and classification tasks, achieving up to 20.7% improvement over greedy decoding, while maintaining general vision-language performance with low computational overhead.

cs.CV↗

arXiv2026

Advanced Externally Seeded FEL Schemes for High-Repetition-Rate Operation at SHINE

Externally seeded free-electron lasers (FELs) are promising approaches for generating fully coherent soft-X-ray radiation. Their extension to shorter wavelengths and MHz-level repetition rates is, however, constrained by the limited availability of high-repetition-rate seed lasers with sufficient energy modulation. Recent self-amplification and direct-amplification experiments at the Shanghai Soft X-ray FEL facility have significantly relaxed the peak-power requirement for high-gain harmonic generation (HGHG) and opened a practical path toward echo-enabled harmonic generation (EEHG). Using the SHINE bypass line, three compatible high-repetition-rate seeded-FEL configurations are explored: self-modulation cascaded HGHG, self-modulation EEHG, and direct-amplification-driven EEHG. Numerical simulations indicate that these schemes can provide flexible routes toward MHz-level operation with harmonic generation beyond the 30th order. A common modulator-chicane layout is proposed to preserve compatibility among the candidate modes and to support future optimization and experimental implementation at SHINE.

physics.acc-ph↗

arXiv2026

Fully coherent short wavelength free-electron laser driven by a single sub-microjoule seed

High-repetition-rate, fully coherent extreme-ultraviolet (EUV) and X-ray free-electron lasers (FELs) are essential for advanced time-resolved ultrafast spectroscopies. While external seeding serves as the standard technique to achieve precise temporal coherence, conventional methods demand hundred-megawatt peak-power laser systems. Furthermore, advanced configurations like echo-enabled harmonic generation (EEHG) introduce the severe complexities of dual-laser synchronization. Together, these requirements fundamentally restrict operations to kilohertz repetition rates and compromise overall system stability. Here, we experimentally demonstrate a fully coherent EEHG-FEL driven by a single, sub-microjoule seed laser. By employing a direct-amplification enabled harmonic generation technique, we utilize an initial 0.4 microJ (2 MW peak power) ultraviolet seed to directly drive coherent lasing at nanometer wavelengths. By eliminating the need for extreme peak powers and multiple synchronized lasers, this approach significantly simplifies the seeding architecture and provides a practical and robust pathway toward megahertz-class, fully coherent EUV and X-ray light sources.

physics.acc-ph↗

arXiv2026

A Short-timescale Negative Optical Continuum Lag in SDSS J083717.88+191647

Continuum reverberation mapping (RM) is a powerful technique for constraining the accretion disk structure in active galactic nuclei (AGNs). In typical cases, the shorter-wavelength emission is used as the reference, and a positive time lag is observed since the inner, hotter regions of the accretion disk respond earlier than the cooler outer regions at longer wavelengths. However, we detect a short-timescale negative inter-band lag in SDSS~J083717.88+191647 using RM techniques, where the \textit{g}-band lags behind the \textit{r}-band emission. The light curves from the Zwicky Transient Facility reveal two distinct phases, a stabilizing and a declining phase, in which the time lags show opposite signs. Using \texttt{JAVELIN} with the $g$-band as the reference, we obtain time lags of $3.68^{+1.94}_{-2.78}$~days during the stabilizing phase and $-1.60^{+0.69}_{-0.54}$~days during the declining phase. Although negative continuum lags have been reported in a few previous studies, the present case is distinguished by its clear phase dependence and the accompanying color evolution. We attribute the observed lag reversal to a moving dust-cloud obscuration scenario, in which the cloud crossing the line of sight preferentially obscures emission from the outer longer-wavelength regions of the disk, causing the $r$-band to decline earlier than the $g$-band and thus producing the observed negative inter-band lag. Our results indicate that AGN variability may be more complex than previously thought. Future high-cadence, multi-band observations will be essential to test this dust-obscuration model and to further explore the interplay between the accretion disk emission and dust in AGNs.

astro-ph.GA↗

arXiv2026

Demonstration of High-Gain Harmonic Lasing in a Terahertz Free-Electron Laser

Compact Free-Electron Lasers (FELs) offering broad, continuous spectral tunability are traditionally constrained by fixed-parameter magnetic structures and the necessity for high-energy electron beams. High-gain Harmonic Lasing (HL) has long been proposed as a solution to overcome these limitations; however, a robust experimental verification of this principle has remained absent. Here, we report the first experimental demonstration of high-gain HL. By employing a frequency-tunable electron beam density modulation to dominate the fundamental instability, we achieved sustained FEL amplification at the 3rd and 5th harmonics of the wiggler. The HL mode generated output power comparable to conventional fundamental operation with enhanced stability and narrower spectral bandwidth. Notably, we demonstrate that HL extends the spectral coverage by a factor of two under fixed facility constraints, achieving pulse energies up to 540 μJ. These results establish high-gain HL as a versatile mechanism for advancing compact, wavelength-flexible FEL facilities.

physics.acc-ph↗

arXiv2026

Balancing Classification and Calibration Performance in Decision-Making LLMs via Calibration Aware Reinforcement Learning

Large language models (LLMs) are increasingly deployed in decision-making tasks, where not only accuracy but also reliable confidence estimates are essential. Well-calibrated confidence enables downstream systems to decide when to trust a model and when to defer to fallback mechanisms. In this work, we conduct a systematic study of calibration in two widely used fine-tuning paradigms: supervised fine-tuning (SFT) and reinforcement learning with verifiable rewards (RLVR). We show that while RLVR improves task performance, it produces extremely overconfident models, whereas SFT yields substantially better calibration, even under distribution shift, though with smaller performance gains. Through targeted experiments, we diagnose RLVR's failure, showing that decision tokens act as extraction steps of the decision in reasoning traces and do not carry confidence information, which prevents reinforcement learning from surfacing calibrated alternatives. Based on this insight, we propose a calibration-aware reinforcement learning formulation that directly adjusts decision-token probabilities. Our method preserves RLVR's accuracy level while mitigating overconfidence, reducing ECE scores up to 9 points.

cs.LG↗

arXiv2025

Journey Before Destination: On the importance of Visual Faithfulness in Slow Thinking

Reasoning-augmented vision language models (VLMs) generate explicit chains of thought that promise greater capability and transparency but also introduce new failure modes: models may reach correct answers via visually unfaithful intermediate steps, or reason faithfully yet fail on the final prediction. Standard evaluations that only measure final-answer accuracy cannot distinguish these behaviors. We introduce the visual faithfulness of reasoning chains as a distinct evaluation dimension, focusing on whether the perception steps of a reasoning chain are grounded in the image. We propose a training- and reference-free framework that decomposes chains into perception versus reasoning steps and uses off-the-shelf VLM judges for step-level faithfulness, additionally verifying this approach through a human meta-evaluation. Building on this metric, we present a lightweight self-reflection procedure that detects and locally regenerates unfaithful perception steps without any training. Across multiple reasoning-trained VLMs and perception-heavy benchmarks, our method reduces Unfaithful Perception Rate while preserving final-answer accuracy, improving the reliability of multimodal reasoning.

cs.CV↗

arXiv2025

Dual core system candidates: a sample of objects with large velocity offset between absorption and narrow emission lines

We present a sample of 28 objects at z<0.3 from Data Release 16 of the Sloan Digital Sky Survey (SDSS DR16) with large velocity offset (> 200 km/s) of narrow H$β$ and H$α$ emission lines relative to absorption lines. Diagnostic classification via the Baldwin-Phillips-Terlevich diagram indicates that the sample comprises 12 AGNs, 12 composite galaxies, 3 H{\sc ii} galaxies, and 1 object of uncertain classification. A strong correlation is found between stellar mass and velocity dispersion. We examine the asymmetries of the narrow H$β$ and find that the correlation between velocity offset and narrow H$β$ skewness is negligible in both blue-shifted and red-shifted systems, suggesting that the rotating disk model may not fully explain the observed kinematics. The sample exhibits an asymmetric velocity offset distribution, with more red-shifted (17) than blue-shifted (11) objects. No significant correlation is observed between velocity offset and line width in blue-shifted systems, while red-shifted systems show a weak anti-correlation for narrow H$α$, which is inconsistent with the outflow model. The similarity in velocity offset between narrow emission lines supports the dual core system. Furthermore, the SDSS photometric images reveal eight objects with two cores and two with merger features. Based on the narrow emission line properties, the objects in our sample represent strong candidates for dual core systems exhibiting velocity offset. Extending this property to higher-redshift populations in the near future may facilitate the identification of merging supermassive black hole pairs at earlier cosmic epochs, providing critical constraints on their formation and evolution.

astro-ph.GA↗

arXiv2025

Rethinking LLM Uncertainty: A Multi-Agent Approach to Estimating Black-Box Model Uncertainty

Quantifying uncertainty in black-box LLMs is vital for reliable responses and scalable oversight. Existing methods, which gauge a model's uncertainty through evaluating self-consistency in responses to the target query, can be misleading: an LLM may confidently provide an incorrect answer to a target query, yet give a confident and accurate answer to that same target query when answering a knowledge-preserving perturbation of the query. We systematically analyze the model behaviors and demonstrate that this discrepancy stems from suboptimal retrieval of parametric knowledge, often due to contextual biases that prevent consistent access to stored knowledge. We then introduce DiverseAgentEntropy, a novel, theoretically-grounded method employing multi-agent interaction across diverse query variations for uncertainty estimation of black-box LLMs. This approach more accurately assesses an LLM's true uncertainty and improves hallucination detection, outperforming existing self-consistency based techniques.

cs.CL↗

arXiv2025

Attosecond Waveform Synthesis through Echo-enabled Harmonic Generation Free-electron Lasers

Attosecond pulse trains (APTs) are indispensable for probing electron dynamics at their intrinsic timescales. High harmonic generation (HHG) has long been a successful and widely used technique in producing extreme ultraviolet APTs. While in the soft X-ray regime, HHG suffers from low conversion efficiency and lacking flexibility in the waveform and spectrum control. Here in this study, based on the waveform synthesis of the echo-enabled harmonic generation (EEHG) free-electron laser (FEL), we propose a novel method that can generate soft X-ray APTs with high temporal and spectral tunability. EEHG scheme is well-known in forming phase-locked high harmonic bunching combs down to the soft X-ray regime. And We can facilitate successive FEL lasing in several different harmonic numbers and then perform the coherent waveform synthesis to generate soft X-ray APTs. Three-dimensional simulation results indicate that reproducible generation of coherent APTs in the soft X-ray regime with peak power of 3.5 GW and micropulse duration of 160 as can be achieved by five-harmonic synthesis. And the micropulse duration together with the spectral components of the APTs can be adjusted easily according to the programmable high harmonic bunching combs in the EEHG scheme. This method has the potential to establish a robust platform for attosecond sciences in the soft X-ray regime, which can enable unprecedented studies of electron dynamics in physical and chemical reactions, biological systems and quantum materials.

physics.acc-ph↗

arXiv2025

SheetMind: An End-to-End LLM-Powered Multi-Agent Framework for Spreadsheet Automation

We present SheetMind, a modular multi-agent framework powered by large language models (LLMs) for spreadsheet automation via natural language instructions. In this paper, we introduce a hierarchical agentic system consisting of three specialized agents: Manager Agent that decomposes complex user instructions into subtasks; an Action Agent that translates these into structured commands using a Backus-Naur Form (BNF) grammar; and a Reflection Agent that validates alignment between generated actions and the user's original intent. We evaluate SheetMind on the 221-task SheetCopilot Benchmark with GPT-3.5-Turbo. SheetMind achieved 100% execution success and 54.8% functional correctness, exceeding SheetCopilot (44.3%) while maintaining perfect execution reliability. We also conduct ablation study on a separately curated dataset to confirm that the full three-agent configuration consistently outperforms all partial variants. Lastly, we integrate our system into Google Sheets via a Workspace extension.

cs.HC↗

arXiv2025

A candidate for True Type-2 AGN without hidden central BLRs Identified by central Tidal Disruption Event

In this manuscript, through applications of TDE (tidal disruption event) expected variability properties, a potential candidate for True type-2 AGN without hidden central broad line regions (=TT2AGN) is reported in the SDSS J233454.07+145712.9 (=SDSS J2334). Through analyzing the 20-years optical light curves of SDSS J2334 from different Sky Survey projects, a TDE is preferred with a $4.7{\rm M_\odot}$ main-sequence star tidally disrupted by the central BH with mass $11.7\times 10^6{\rm M_\odot}$, indicating that central region within distance about 20 light-days to central BH in SDSS J2334 is directly in the line-of-sight. Moreover, AGN activities in SDSS J2334 can be confirmed through applications of BPT diagrams. Meanwhile, comparing virial BH mass determined through assumed broad Balmer emission components and M-sigma expected BH mass by well measured stellar velocity dispersion through stellar absorption features, optical broad emission lines in SDSS J2334 are disfavored with confidence level higher than 6$σ$. Therefore, combining the unique properties of the TDE and the spectroscopic results with only narrow emission lines, SDSS J2334 can be well identified as a potential candidate for a TT2AGN. The results indicate the to detect TDE expected flares in normal Type-2 AGN classified by spectroscopic results should be a new practicable method for identifying

astro-ph.GA↗

arXiv2025

First Lasing and Stable Operation of a Direct-Amplification Enabled Harmonic Generation Free-Electron laser

Seeded free-electron lasers (FELs) capable of operating at repetition rates up to the MHz level are in high demand for advanced time-resolved spectroscopies, which require both full longitudinal coherence and high average photon flux in the extreme ultraviolet (EUV) and x-ray regimes. However, conventional external-seed laser systems cannot sustain MHz operation with sufficient hundreds of megawatts peak power requirement due to their limited total power. Here, we report the first lasing and stable operation of a direct-amplification-enabled harmonic generation FEL driven by a weak seed laser with MW-level peak power. Beginning with an ultraviolet seed laser with only 0.75 μJ pulse energy, we demonstrate its direct amplification to over 10 μJ within an 8-meter-long modulator. We observe coherent harmonic generation up to the 12th harmonic of the seed and achieve saturation of the 7th harmonic in the radiator. These results represent a crucial milestone toward the realization of MHz-class, fully coherent EUV and x-ray light sources.

physics.acc-ph↗

arXiv2025

Open Domain Question Answering with Conflicting Contexts

Open domain question answering systems frequently rely on information retrieved from large collections of text (such as the Web) to answer questions. However, such collections of text often contain conflicting information, and indiscriminately depending on this information may result in untruthful and inaccurate answers. To understand the gravity of this problem, we collect a human-annotated dataset, Question Answering with Conflicting Contexts (QACC), and find that as much as 25% of unambiguous, open domain questions can lead to conflicting contexts when retrieved using Google Search. We evaluate and benchmark three powerful Large Language Models (LLMs) with our dataset QACC and demonstrate their limitations in effectively addressing questions with conflicting information. To explore how humans reason through conflicting contexts, we request our annotators to provide explanations for their selections of correct answers. We demonstrate that by finetuning LLMs to explain their answers, we can introduce richer information into their training that guide them through the process of reasoning with conflicting contexts.

cs.CL↗

arXiv2025

Towards Long Context Hallucination Detection

Large Language Models (LLMs) have demonstrated remarkable performance across various tasks. However, they are prone to contextual hallucination, generating information that is either unsubstantiated or contradictory to the given context. Although many studies have investigated contextual hallucinations in LLMs, addressing them in long-context inputs remains an open problem. In this work, we take an initial step toward solving this problem by constructing a dataset specifically designed for long-context hallucination detection. Furthermore, we propose a novel architecture that enables pre-trained encoder models, such as BERT, to process long contexts and effectively detect contextual hallucinations through a decomposition and aggregation mechanism. Our experimental results show that the proposed architecture significantly outperforms previous models of similar size as well as LLM-based models across various metrics, while providing substantially faster inference.

cs.CL↗

arXiv2025

Enabling Continuous THz Band Coverage via Precise Electron Beam Tailoring in Free-electron Lasers

High-power, continuously tunable narrowband terahertz (THz) sources are essential for advancing nonlinear optics, THz-driven material dynamics, and ultrafast spectroscopy. Conventional techniques typically impose a trade-off between pulse energy and frequency tunability. Here, we introduce a novel free-electron laser approach that overcomes these limitations by pre-modulating a relativistic electron beam with a frequency-beating laser pulse and leveraging bunch compression along with collective effects to enhance microbunching. Experimental results demonstrate that this technique generates narrowband THz emission with continuous frequency tunability from 7.8 to 30.8THz, achieving pulse energies up to 385μJ while maintaining spectral bandwidths between 7.7% and 14.7%. Moreover, the method exhibits exceptional robustness and scalability, highlighting its unique ability to bridge the long-standing THz gap and offering a promising solution for diverse cutting-edge scientific applications.

physics.acc-ph↗