4 papers
Document Optimization for Black-Box Retrieval via Reinforcement Learning
Omri Uzan, Ron Polonsky, Douwe Kiela +1
Document expansion is a classical technique for improving retrieval quality, and is attractive since it shifts computation offline, avoiding additional query-time processing. Howev…
Guided Query Refinement: Multimodal Hybrid Retrieval with Test-Time Optimization
Omri Uzan, Asaf Yehudai, Roi pony +2
Multimodal encoders have pushed the boundaries of visual document retrieval, matching textual query tokens directly to image patches and achieving state-of-the-art performance on p…
CharBench: Evaluating the Role of Tokenization in Character-Level Tasks
Omri Uzan, Yuval Pinter
Tasks that require character-level reasoning, such as counting or locating characters within words, remain challenging for contemporary language models. A common conjecture is that…
Tokenization Is More Than Compression
Craig W. Schmidt, Varshini Reddy, Haoran Zhang +4
Tokenization is a foundational step in natural language processing (NLP) tasks, bridging raw text and language models. Existing tokenization approaches like Byte-Pair Encoding (BPE…