7 papers
Optimize Cheap, Deploy Strong: Cost-Aware Cross-Tier Transfer for Evolutionary Optimization
Tal Oved, Roi Pony, Oshri Naparstek +1
Evolutionary optimization of LLM prompts and agentic programs (e.g., GEPA) is dominated by fitness evaluation: scoring each candidate runs an answering LLM over a validation set, s…
FLASH-MAXSIM: IO-Aware Fused Kernels for Late-Interaction Retrieval
Roi Pony, Daniel Ezer, Adi Raz Goldfarb +3
Late-interaction retrieval (ColBERT, ColPali) scores a query against a document via the MaxSim operator. The standard PyTorch implementation materialises the full query-token x doc…
Col-Bandit: Query-Time Top- Estimation for Late-Interaction Retrieval
Roi Pony, Adi Raz Goldfarb, Oshri Naparstek +3
Multi-vector late-interaction retrievers such as ColBERT achieve state-of-the-art quality, but their query-time cost is dominated by exhaustively computing token-level MaxSim inter…
Is the Modality Gap a Bug or a Feature? A Robustness Perspective
Rhea Chowers, Oshri Naparstek, Udi Barzelay +1
Many modern multi-modal models (e.g. CLIP) seek an embedding space in which the two modalities are aligned. Somewhat surprisingly, almost all existing models show a strong modality…
VAREX: A Benchmark for Multi-Modal Structured Extraction from Documents
Udi Barzelay, Ophir Azulai, Inbar Shapira +4
We introduce VAREX (VARied-schema EXtraction), a benchmark for evaluating multimodal foundation models on structured data extraction from government forms. VAREX employs a Reverse…
REAL-MM-RAG: A Real-World Multi-Modal Retrieval Benchmark
Navve Wasserman, Roi Pony, Oshri Naparstek +4
Accurate multi-modal document retrieval is crucial for Retrieval-Augmented Generation (RAG), yet existing benchmarks do not fully capture real-world challenges with their current d…