FOSTER: First-order Dataset Distillation for Text-based Sequential Recommendation
2026-06-01T08:52:38Z•ba50e56bbc1a021662f4c291e9aae406eb4104b710d5d1dd583f4a3255bda256
DCRCDynaTreeFOSTERGraph-GRPOLLM-hallucinationsMIMORAGV-SPLADEagentic-RAGanswer-retentionbanditscitation-stanceclaim-networkcontextual-thompson-samplingcredit-assignmentdata-centricdataset-distillationfinancial-QAinformation-retrievalknowledge-graphmachine-learningmultilingual-IRrecommendation-systemsretrieval-augmented-generationvisual-document-retrieval
What happened
Collection of recent ML/IR papers (arXiv, 01 Jun 2026) covering dataset distillation for text-based sequential recommendation (FOSTER), representation effects in Retrieval-Augmented Generation (RAG) with a focus on answer retention, an inference-free multimodal sparse retriever for large-scale visual-document search (V-SPLADE), a typed claim network for citation stance and analytic tasks, dependency-aware credit assignment for LLM chain-of-thought in e-commerce relevance (Graph-GRPO), a data-centric reasoning compiler to reduce numerical hallucinations in financial QA (DCRC), multilingual IR (
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_ir
- Record identifier
- ba50e56bbc1a021662f4c291e9aae406eb4104b710d5d1dd583f4a3255bda256
- Enrichment time
- 2026-06-01T08:52:38Z
- AI-assisted enrichment
- Yes
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