arxiv arXiv cs.CL · 47d ago · src: 51d ago · research

CAT-Translate: Compact Japanese-English Models Outperform Multilingual Ones in Real-World Tasks

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CAT-Translate introduces a family of small, open-source models specialized for Japanese-English translation. Using synthetic parallel corpora and a two-stage fine-tuning approach, the models achieve superior performance on real-world benchmarks across business, legal, medical, financial, and patent domains, outperforming large multilingual models in practical applications.

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arxiv arXiv cs.CL · 47d ago · 1 view

Beaver: Agent Harness for Scientific Curation from Multimodal Sources

Beaver is an agent harness that extracts structured information from scientific papers by integrating multimodal evidence tooling, task scaffolding, and artifact-grounded autoresearch. It achieves 81.0 on the Gold-Referenced Attribute Score, outperforming frontier agents by over 23 points, with key gains on high-value attributes requiring cross-modal reasoning.

arxiv arXiv cs.AI · 51d ago · 1 view

See-and-Reach: Vision-Language Navigation for UAVs in Field of View

UAV-VLN-FOV isolates the see-and-reach stage for precise evaluation of UAV navigation. 3DG-VLN enhances visual grounding and spatial alignment using dynamic 3D direction cues, achieving a 13.82% success rate improvement over baselines and validated in real-world trials.

arxiv arXiv cs.AI · 51d ago

Hidden Evolution of Disguised Visual Context in VLMs

Visual tokens enter large language models as raw, unstructured signals. Their internal transformation and integration depend on architecture—either as in-context prompts or injected into intermediate layers—leading to distinct evolution paths in visual representation and frequency characteristics. We find that attention alone is insufficient; performance is driven by the quality of visual representations at each layer across different integration paradigms.

arxiv arXiv cs.AI · 51d ago · 1 view

IHUBERT: Persian Pretrained Model with Semantic Deduplication

IHUBERT is a monolingual Persian pretrained language model trained on a 45 GB curated subset of the Sepahr-Danesh collection. It uses vector-based semantic deduplication and a domain-balanced pretraining pipeline to improve corpus quality and reduce redundancy, achieving top performance in extractive question answering and strong results in NER and topic classification, though relation extraction remains a challenge.

arxiv arXiv cs.CL · 51d ago · 2 views

JAMER: Project-Level Code Framework Dataset and Benchmark

JAMER introduces JamSet and JamBench, the first project-level game code dataset and benchmark on a professional game engine. Built from 8,133 verified Game Jam projects, it enables deterministic evaluation and reveals a capability cliff in AI models as project scale increases, with runtime pass rates dropping from 80.4% to 5.7%.