250 citations · 366 across the 47 of their papers we have counts for
41 papers · 1 filter
Building Multilingual Bridges: Data Mixing as the Pillar of Generalization for In-Language Reasoning
Mehrnaz Mofakhami, Ananya Sahu, Alejandro R. Salamanca +5
Reasoning language models have made substantial advances on a variety of complex tasks, yet their capabilities remain overwhelmingly English-centric: models primarily reason in Eng…
The IOL-AI Challenge: An Open Challenge towards Advancing Linguistic Reasoning
Eduardo Sánchez, Rita Berrada, Dan-Mircea Mirea +8
Reasoning in LLMs is overwhelmingly studied in domains that provide a model with rules: mathematics and code. Linguistic puzzles invert this: the solver must first discover the sys…
CALIBER: Calibrating Confidence Before and After Reasoning in Language Models
Conor Finlay, Joshua Kurien, Saurabh Dash +2
Reasoning language models are increasingly asked not only to answer difficult questions, but also to estimate their likelihood of success. Existing methods typically elicit confide…
The Culture Funnel: You Can't Align What isn't in the Data
Ananya Sahu, Mehrnaz Mofakhami, Daniel D'Souza +3
Current cultural alignment approaches focus on inference-time interventions, assuming models already contain sufficient cultural knowledge. We argue modern LLM pipelines suffer fro…
Soft-SVeRL: Self-Verified Reinforcement Learning with Soft Rewards
Saurabh Dash, Pierre Clavier, John Dang +4
Reinforcement Learning from Verifiable Rewards (RLVR) has improved language models in domains such as mathematics and code, where correctness can be checked automatically. However,…
Tiny Aya: Bridging Scale and Multilingual Depth
Alejandro R. Salamanca, Diana Abagyan, Daniel D'souza +23
Tiny Aya redefines what a small multilingual language model can achieve. Trained on 70 languages and refined through region-aware posttraining, it delivers state-of-the-art in tran…
Unlocking Reasoning Capability on Machine Translation in Large Language Models
Sara Rajaee, Sebastian Vincent, Alexandre Berard +3
Reasoning-oriented large language models (RLMs) achieve strong gains on tasks such as mathematics and coding by generating explicit intermediate reasoning. However, their impact on…
The Art of Asking: Multilingual Prompt Optimization for Synthetic Data
David Mora, Viraat Aryabumi, Wei-Yin Ko +3
Synthetic data has become a cornerstone for scaling large language models, yet its multilingual use remains bottlenecked by translation-based prompts. This strategy inherits Englis…
Making, not Taking, the Best of N
Ammar Khairi, Daniel D'souza, Marzieh Fadaee +1
Obtaining high-quality generations in modern LLMs has largely been framed as a selection problem: identifying a single winning generation from a diverse pool of N samples, the Best…
NeoBabel: A Multilingual Open Tower for Visual Generation
Mohammad Mahdi Derakhshani, Dheeraj Varghese, Marzieh Fadaee +1
Text-to-image generation advancements have been predominantly English-centric, creating barriers for non-English speakers and perpetuating digital inequities. While existing system…
One Tokenizer To Rule Them All: Emergent Language Plasticity via Multilingual Tokenizers
Diana Abagyan, Alejandro R. Salamanca, Andres Felipe Cruz-Salinas +6
Pretraining massively multilingual Large Language Models (LLMs) for many languages at once is challenging due to limited model capacity, scarce high-quality data, and compute const…
The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating It
Zheng-Xin Yong, Beyza Ermis, Marzieh Fadaee +2
This paper presents a comprehensive analysis of the linguistic diversity of LLM safety research, highlighting the English-centric nature of the field. Through a systematic review o…
Aya Vision: Advancing the Frontier of Multilingual Multimodality
Saurabh Dash, Yiyang Nan, John Dang +22
Building multimodal language models is fundamentally challenging: it requires aligning vision and language modalities, curating high-quality instruction data, and avoiding the degr…
Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation
Israfel Salazar, Manuel Fernández Burda, Shayekh Bin Islam +42
The evaluation of vision-language models (VLMs) has mainly relied on English-language benchmarks, leaving significant gaps in both multilingual and multicultural coverage. While mu…
A Post-trainer's Guide to Multilingual Training Data: Uncovering Cross-lingual Transfer Dynamics
Luisa Shimabucoro, Ahmet Ustun, Marzieh Fadaee +1
In order for large language models to be useful across the globe, they are fine-tuned to follow instructions on multilingual data. Despite the ubiquity of such post-training, a cle…
Command A: An Enterprise-Ready Large Language Model
Team Cohere, :, Aakanksha +227
In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases. Command A is an agent-optimised…
Déjà Vu: Multilingual LLM Evaluation through the Lens of Machine Translation Evaluation
Julia Kreutzer, Eleftheria Briakou, Sweta Agrawal +2
Generation capabilities and language coverage of multilingual large language models (mLLMs) are advancing rapidly. However, evaluation practices for generative abilities of mLLMs a…
Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study
Menglong Cui, Pengzhi Gao, Wei Liu +2
Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. I…
From Tools to Teammates: Evaluating LLMs in Multi-Session Coding Interactions
Nathanaël Carraz Rakotonirina, Mohammed Hamdy, Jon Ander Campos +5
Large Language Models (LLMs) are increasingly used in working environments for a wide range of tasks, excelling at solving individual problems in isolation. However, are they also…
Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier
John Dang, Shivalika Singh, Daniel D'souza +42
We introduce the Aya Expanse model family, a new generation of 8B and 32B parameter multilingual language models, aiming to address the critical challenge of developing highly perf…
Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation
Shivalika Singh, Angelika Romanou, Clémentine Fourrier +21
Cultural biases in multilingual datasets pose significant challenges for their effectiveness as global benchmarks. These biases stem not only from differences in language but also…
INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge
Angelika Romanou, Negar Foroutan, Anna Sotnikova +56
The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal val…
Mix Data or Merge Models? Optimizing for Diverse Multi-Task Learning
Aakanksha, Arash Ahmadian, Seraphina Goldfarb-Tarrant +3
Large Language Models (LLMs) have been adopted and deployed worldwide for a broad variety of applications. However, ensuring their safe use remains a significant challenge. Prefere…
M-RewardBench: Evaluating Reward Models in Multilingual Settings
Srishti Gureja, Lester James V. Miranda, Shayekh Bin Islam +7
Reward models (RMs) have driven the state-of-the-art performance of LLMs today by enabling the integration of human feedback into the language modeling process. However, RMs are pr…