Semantic Retrieval for Product Search
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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...
Beyond Matching: Category-Guided Latent Intent Reasoning for Generative Retrieval in E-Commerce
Announce Type: new Abstract: Generative retrieval offers a new paradigm for e-commerce search by mapping user queries directly to product Semantic Identifiers (SIDs). However, e-commerce queries are often short, noisy, attribute-heavy, and associated with multiple category-consistent products, creating a substantial representation gap between natural-language shopping intent and artificially constructed item SIDs. Explicit Chain-of-Thought (CoT) reasoning can help bridge this gap, but its...
BEATS: Bootstrapping E-commerce Attribute Taxonomies for Search through Iterative Human-AI Collaboration
Announce Type: new Abstract: E-commerce platforms in emerging markets often operate with underdeveloped product catalogs that contain only category taxonomies but lack structured attribute schemas. This absence of fine-grained product attributes limits search capabilities -- preventing faceted filtering, degrading query understanding, and weakening semantic representations used by search systems. We present BEATS, a human-in-the-loop LLM framework for bootstrapping product attribute...
The Evolution of 'More Like This'
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Projection and Quantisation: A Unifying View of Learning to Hash, from Random Projections to the RAG Era
arXiv:2510.04127v2 Announce Type: replace Abstract: Approximate nearest neighbour (ANN) search underpins large-scale retrieval, increasingly within the retrieval-augmented generation pipelines that ground large language models, yet the methods that address it have multiplied across communities until they are seldom read as a single field. We argue they form one field with three design choices, and develop the projection-quantisation-organisation (PQO) lens, under which locality-sensitive...
Rethinking Search as Code Generation
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Trading Engagement for Sustainability: Carbon-Aware Re-ranking for E-commerce Recommendations
arXiv:2606.04550v1 Announce Type: new Abstract: E-commerce recommender systems strongly influence which products users consider and purchase, yet sustainability signals such as Product Carbon Footprint (PCF) are almost never available at catalog scale. We study carbon-aware product recommendation in the realistic setting where PCF labels are missing for most items and must be inferred. We first estimate product-level carbon footprints via a retrieval-augmented PCF estimation pipeline that...
Launch HN: Hyper (YC P26) – Company brain to power agentic development
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Context-as-a-Service: Surfacing Cross-File Dependency Chains for LLM-Generated Developer Documentation
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