Papers arxiv:2605.12438 A Causal Language Modeling Detour Improves Encoder Continued Pretraining Published on May 12 Submitted by Rian Touchent on May 13 ALMAnaCH Inria Authors: Rian Touchent , Abstract Switching from Masked Language Modeling to Causal Language Modeling during encoder adaptation im… …
Papers arxiv:2605.07075 ModelLens: Finding the Best for Your Task from Myriads of Models Published on May 8 Submitted by Rui Yanson Cai on May 11 UC Davis Authors: Rui Cai , , Xiaofei Wen , , , , , Abstract ModelLens is a unified framework that recommends models in real-world scenarios by learning … …
… Please check your model and dataset." ValueError: The dataset appears to be vision-related contains 'image' or 'images' keys , but the provided model does not seem to be a vision-language model. Please check your model and dataset.
… This one worked: https://huggingface.co/mistralrs-community/models · welcome to new ai video generator: happyhorse ai https://happyhorse-ai.co Thanks a lot @ pamaru and @ patrickdeanbrown , those links will be fixed when this PR is merged 🙌 I’ve made history I'm impressed, extremely intelligent mod… …
… The following papers were recommended by the Semantic Scholar API Teaching Thinking Models to Reason with Tools: A Full-Pipeline Recipe for Tool-Integrated Reasoning 2026 Think Anywhere in Code Generation 2026 HintMR: Eliciting Stronger Mathematical Reasoning in Small Language Models 2026 Efficient… …
… Get this paper in your agent: hf papers read 2605.11680 Don't have the latest CLI? curl -LsSf https://hf.co/cli/install.sh | bash No model linking this paper Cite arxiv.org/abs/2605.11680 in a model README.md to link it from this page. …
… Get this paper in your agent: hf papers read 2605.10434 Don't have the latest CLI? curl -LsSf https://hf.co/cli/install.sh | bash No model linking this paper Cite arxiv.org/abs/2605.10434 in a model README.md to link it from this page. …
… Too many “reasoning models” gloss over those operational details, which matter a lot once you leave the demo stage. As someone working across text, vision, and creative tooling, I also appreciate how releases like this pair well with the broader AI stack. …
… We evaluate our model on four standard relation extraction benchmarks: CoNLL04 , DocRED , FewRel , and CrossRE , and demonstrate competitive performance against both specialized relation extraction models and large language models, while maintaining the computational efficiency characteristic of th… …
… On this subset, no model exceeds 50%, identifying refusal as a new optimization target that current models do not directly address. To prevent contamination, the dataset will be publicly released in late 2026, with model evaluations available upon request in the interim. …