activity
20172026
most citedOMPGPT: A Generative Pre-trained Transformer Model for OpenMP

24 citations · 56 across the 45 of their papers we have counts for

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Showing 2026Show all

6 papers · 1 filter

cs.CV2026

Texture Interpolation as Texton Matching

Ido Madar, Gal Oren, Shai Avidan

Texture interpolation asks what should lie between two textures. Standard methods typically blend pixels or features at corresponding spatial locations, implicitly assuming that co…

cs.AI2026

ParBench: A Benchmark for Reliable Evaluation of LLM Parallel Code Translation

Samyak Jhaveri, Erel Kaplan, Tom Yotam +4

Modern compute-intensive software must migrate across a changing ecosystem of accelerators, programming APIs, compiler stacks, and portability layers, including CUDA, OpenMP, OpenC…

cs.CV2026

Where Does Texture Evidence Live in SAM? Features, Proposal Masks, and Texture Segmentation

Nadav Orenstein, Aviad Cohen Zada, Shai Avidan +1

Texture segmentation stresses foundation segmentation because meaningful regions are defined by material or repeated appearance rather than object identity. Segment Anything Models…

cs.CV2026

Sub-Semantic Image Segmentation

Aviad Cohen Zada, Nadav Orenstein, Shai Avidan +1

Images can be segmented based on visual cues (i.e., texture segmentation) or into objects (i.e., semantic segmentation). We propose a new category of sub-semantic image segmentatio…

cs.DC2026

Latent Reasoning Guidance for Parallel Code Translation

Tomer Bitan, Erel Kaplan, Roee Bar-Yadin +5

Tackling complex coding tasks often requires autonomous agents and iterative repair pipelines. These increasingly rely on large amounts of test-time computation, often spending man…

cs.DC2026

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

Erel Kaplan, Tomer Bitan, Lian Ghrayeb +4

Parallel programming is central to HPC and AI, but producing code that is correct and fast remains challenging, especially for OpenMP GPU offload, where data movement and tuning do…