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Related Articles from SNS
Semantic Retrieval for Product Search in E-Commerce
arXiv:2606.01504v1 Announce Type: new Abstract: Semantic retrieval in e-commerce must handle short, noisy, and colloquial queries over large product catalogs with fine-grained attribute distinctions. We present a Siamese LLM dual-encoder trained through a two-stage pipeline: contrastive learning with a false-negative margin mask to prevent penalization of near-duplicate products, followed by Relative Odds Alignment for Retrieval (ROAR), a preference optimization objective that extends...
Cross Paraphrastic Invariance Learning for Hallucination Detection
arXiv:2606.08157v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate hallucinations, which are unsupported by a source document. To avoid costly LLM-as-evaluator pipelines and the heavy annotation demands of existing classifiers, we propose CPIL (Cross Paraphrastic Invariance Learning), a two-stage Siamese framework that maximizes the utility of existing labeled data. Concretely, CPIL constructs informative training pairs by: (i) generating paraphrastic views of...
Self-Supervised Learning with a Multi-Task Latent Space Objective
Announce Type: replace Abstract: We propose a multi-task formulation of self-predictive Siamese SSL in which each spatial transformation defines a distinct latent-space alignment task, solved by a dedicated predictor over a shared encoder. This perspective directly explains a long-standing failure of multi-crop training in self-predictive methods such as BYOL, SimSiam, and MoCo v3: a shared predictor is forced to solve heterogeneous alignment tasks simultaneously, leading to unstable...
From Chiang Mai’s black house to the Bangkok skyline: Inside 137 Pillars
From Chiang Mai’s black house to the Bangkok skyline: Inside 137 Pillars A derelict teak house in Chiang Mai became the unlikely beginning of 137 Pillars, linking a heritage hotel in Wat Ket with a sky-high Sukhumvit address. Chiang Mai locals called it Baan Dam – the Black House. Stand in the grounds today of 137 Pillars House and you would never guess the name.
Bridging the Gap Between Natural Language and Market Dynamics via High-Dimensional Representation Learning
arXiv:2605.30652v1 Announce Type: new Abstract: Traditional multi-modal financial forecasting often relies on scalar sentiment scores, which fail to capture the nuances of financial news. To address this information loss, this paper explores high-dimensional representation learning by replacing discrete polarity ratings with dense FinBERT embeddings within a Transformer-based forecasting architecture. We benchmarked various embedding strategies on the FNSPID dataset, including raw...
Constraint-Aware Optimization for Robust Protein Stability Prediction
Announce Type: new Abstract: Multimodal $\Delta\Delta G$ predictors integrating protein language models with inverse-folding representations achieve strong in-distribution accuracy on the Megascale dataset but exhibit limited robustness on out-of-distribution (OOD) proteins, persistent forward-reverse bias on paired-mutation benchmarks, and under-representation of rare stabilizing mutations. Existing approaches address these limitations primarily through additional architectural components,...