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Xuyang Sun

Publications and source records attributed to Xuyang Sun.

4 recordsLinked to original sources

UniVA: Unified Value Alignment for Generative Recommendation in Online Advertising at Tencent

Generative Recommendation (GR) reformulates recommendation as next-token generation over item Semantic IDs (SIDs) and has shown promise in industrial applications. However, extending GR to advertising is non-trivial, as advertising recommendation must jointly account for user relevance and commercial value. This creates a mismatch: high generation likelihood does not necessarily imply high advertising utility. As a result, valuable ads may be poorly distinguished in the SID space, pruned during autoregressive decoding, or missed when request-invalid branches consume limited beam capacity during online serving. To address this problem, we propose UniVA, a Unified Value Alignment framework for generative advertising recommendation. UniVA aligns commercial value across the entire pipeline of SID construction, autoregressive decoding, and online serving. Commercial SID Tokenization injects business attributes and bid information into SID construction. A Generation-as-Ranking SID Decoder then fuses generation scores with token-level value estimates during autoregressive decoding. {Finally, Value-Aware Constrained Serving restricts the fused decoding process to request-valid SID paths through a personalized trie.} Experiments on the Tencent WeChat Channels advertising platform show that UniVA achieves a 37.04\% relative improvement in offline Hit Rate@100 over the baseline and lifts gross merchandise value (GMV) by 1.5\% in online A/B tests.

cs.IR

Remote Interference Mitigation through Null Precoding and Fractional Programming

With the rapid deployment of 5G systems, remote interference (RI) caused by atmospheric ducting has emerged as an occasional, but critical challenge. This phenomenon occurs when the downlink (DL) signals from distant base stations (BSs) propagate over long distances through tropospheric ducting, severely disrupting uplink (UL) reception at local BSs. To address this challenge, we analyze the effect of RI on network performance, including the channel estimation phase. We then develop a solution that identifies the angle-of-arrival (AOA) estimation of RI and designs precoders and combiners that mitigate RI. Our approach employs interference cancellation techniques through null precoding and fractional programming which enhance the performance of the network. Interestingly, we show that using our scheme, uplink communication is possible at low transmit power regimes that were unusable due to RI. Our results further show a 5.23~dB reduction in normalized mean square error for channel estimation and achieved data rates around 5.8~bit/s/Hz at the previously unusable low uplink transmit power conditions.

cs.IT

Channel Estimation with Asynchronous Reception for User-Centric Cell-Free MIMO Systems

The user-centric, cell-free wireless network is a promising next-generation communication system, but signal synchronization issues arise due to distributed access points and lack of cellular structure. We propose a novel method to recover synchronous pilot reception by introducing new pilot sequences and a matched filter window, enabling orthogonality even with asynchronous reception. Our approach mimics synchronous transmission by extending training sequences. Analysis shows asynchronous reception's impact on channel estimation, and our method significantly improves performance with a small increase of training time overhead. Results demonstrate a 7.26 dB reduction in normalized mean square error and 40% increase in data rate, achieving performance levels comparable to the synchronous case.

cs.IT

Trapping microswimmers in acoustic streaming flow

The acoustofluidic method holds great promise for manipulating microorganisms. When exposed to the steady vortex structures of acoustic streaming flow, these microorganisms exhibit intriguing dynamic behaviors, such as hydrodynamic trapping and aggregation. To uncover the mechanisms behind these behaviors, we investigate the swimming dynamics of both passive and active particles within a two-dimensional acoustic streaming flow. By employing a theoretically calculated streaming flow field, we demonstrate the existence of stable bounded orbits for particles. Additionally, we introduce rotational diffusion and examine the distribution of particles under varying flow strengths. Our findings reveal that active particles can laterally migrate across streamlines and become trapped in stable bounded orbits closer to the vortex center, whereas passive particles are confined to movement along the streamlines. We emphasize the influence of the flow field on the distribution and trapping of active particles, identifying a flow configuration that maximizes their aggregation. These insights contribute to the manipulation of microswimmers and the development of innovative biological microfluidic chips.

physics.flu-dyn