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cs.CL2026
Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models
Victor Conchello Vendrell, Arnau Padres Masdemont, Niccolò Grillo +3
Recurrent LLM architectures have emerged as a promising approach for improving reasoning, as they enable multi-step computation in the embedding space without generating intermedia…
cs.CL2026
M3Kang: Evaluating Multilingual Multimodal Mathematical Reasoning in Vision-Language Models
Aleix Torres-Camps, Nathaniel Mitrani Hadida, Víctor Conchello Vendrell +3
Despite state-of-the-art vision-language models (VLMs) have demonstrated strong reasoning capabilities, their performance in multilingual mathematical reasoning remains underexplor…