E-SENS: Exclusion-Sensitive Penalization for Negative-Constraint Retrieval

arXiv:2608.30130 · cs.IR, cs.AI · Submitted 2026-08-31 · Read on arXiv

cs.IR, cs.AI

Submitted: 2026-08-31

Updated: 2026-09-04

Terminology

• Embeddings — 5× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Actor — 1× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
• BoolQuestions: Does Dense Retrieval Understand Boolean Logic in Language?
• DEO: Training-Free Direct Embedding Optimization for Negation-Aware Retrieval
• Negation is Not Semantic: Diagnosing Dense Retrieval Failure Modes for Trade-offs in Contradiction-Aware Biomedical QA
• ExcluIR: Exclusionary Neural Information Retrieval

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