Papers with real-time scenarios
RTSM: Knowledge Distillation with Diverse Signals for Efficient Real-Time Semantic Matching in E-Commerce (2025.naacl-industry)
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| Challenge: | e-commerce product search is a key component of product discovery and sales in ecommerce . high computational demands of large transformer models pose challenges for their deployment in real-time scenarios. |
| Approach: | They propose a framework for real-time semantic matching that leverages both soft labels from a teacher model and ground truth generated from pairwise query-product and query-query signals. |
| Outcome: | The proposed framework outperforms teacher models and state-of-the-art models on e-commerce datasets. |
Adaptive Simultaneous Sign Language Translation with Confident Translation Length Estimation (2024.lrec-main)
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| Challenge: | Existing non-simultaneous sign language translation methods suffer from inherent inference delays in real-time scenarios. |
| Approach: | They propose an adaptive policy for simultaneous sign language translation that progressively converts incrementally received sign video into its corresponding natural sentence. |
| Outcome: | The proposed policy excels in situations requiring extremely low latency. |
From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models (2026.findings-acl)
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| Challenge: | Existing definitions of streaming LLMs are fragmented and lack a systematic taxonomy . large language models are pre-trained on static and full-context corpora . |
| Approach: | They propose a systematic taxonomy of current streaming Large Language Models and propose underlying methodologies for streaming LLMs. |
| Outcome: | The proposed model is based on data flow and dynamic interaction to clarify existing ambiguities. |
SEE: Signal Embedding Energy for Quantifying Noise Interference in Large Audio Language Models (2026.acl-long)
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| Challenge: | Existing studies on noise lack quantitative analysis and rely on intuition and empirical observation, thus failing to understand practical robustness. |
| Approach: | They propose a method for quantifying the impact of noise intensity on LALM inputs by using a structured activation subspace derived from the model's internal representations. |
| Outcome: | The proposed method outperforms existing denoising methods and demonstrates that noise is perceived more accurately than raw audio features. |
Benchmarking and Enabling Efficient Chinese Medical Retrieval via Asymmetric Encoders (2026.acl-long)
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| Challenge: | Effective medical text retrieval requires high accuracy and low latency. |
| Approach: | They propose a benchmark for medical text retrieval in Chinese using a symmetric architecture . CARE is a lightweight encoder with an LLM-based encoder for offline document encoding . |
| Outcome: | The proposed benchmark surpasses state-of-the-art symmetric models on CMedTEB . it matches high retrieval quality without increasing latency, and it performs well on a single GPU . |