Cohere · Research

Research listings from Cohere on TechiSeek. 142 public listings.

• Treasure Hunt: Real-time Targeting of the Long Tail using Training-Time Markers (Cohere)
  One of the most profound challenges of modern machine learning is performing well on the long-tail of rare and underrepresented features.
• How Does Quantization Affect Multilingual LLMs? (Cohere)
  Quantization techniques are widely used to improve inference speed and deployment of large language models.
• Goodtriever: Adaptive Toxicity Mitigation with Retrieval-augmented Models (Cohere)
  Goodtriever: Adaptive Toxicity Mitigation with Retrieval-augmented Models Toxicity definitions evolve and change over time.
• BERT-as-a-Judge: A Robust Alternative to Lexical Methods for Efficient Reference-Based LLM (Cohere)
  Accurate evaluation is central to the large language model (LLM) ecosystem, guiding model selection and downstream adoption across diverse…
• Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models (Cohere)
  As Large Language Models (LLMs) have become more advanced, they have outpaced our abilities to accurately evaluate their quality.
• Large Language Models are not Zero Shot Communicators (Cohere)
  Oct 26, 2022 Large Language Models are not Zero Shot Communicators Investigating the implicature gap in Large Language Models.
• The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating It (Cohere)
  This paper presents a comprehensive analysis of the linguistic diversity of LLM safety research, highlighting the English-centric nature of…
• Tools Fail: Detecting Silent Errors in Faulty Tools (Cohere)
  Tools have become a mainstay of LLMs, allowing them to retrieve knowledge not in their weights, to perform tasks on the web, and even to co…
• IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models (Cohere)
  Despite the widespread adoption of Large language models (LLMs), their remarkable capabilities remain limited to a few high-resource langua…
• Crosslingual Reasoning through Test-Time Scaling (Cohere)
  Reasoning capabilities of large language models are primarily studied for English, even when pretrained models are multilingual.
• INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge (Cohere)
  Nov 29, 2024 INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge In this work, we construct an evaluation suite…
• Scalable Training of Language Models using PAX pjit and TPUv4 (Cohere)
  Modern large language models require distributed training strategies due to their size.
• Fairness of Deep Ensembles: On the interplay between per-group task difficulty and (Cohere)
  Ensembling is commonly regarded as an effective way to improve the general performance of models in machine learning, while also increasing…
• When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale (Cohere)
  Large volumes of text data have contributed significantly to the development of large language models (LLMs) in recent years.
• Intriguing Properties of Quantization at Scale (Cohere)
  Emergent properties have been widely adopted as a term to describe behavior not present in smaller models but observed in larger models.
• Understanding Likelihood Over-optimisation in Direct Alignment Algorithms (Cohere)
  Direct Alignment Algorithms (DAAs), such as Direct Preference Optimisation (DPO) and Identity Preference Optimisation (IPO), have emerged a…
• The PRISM Alignment Project: What Participatory, Representative and Individualised Human Feedback (Cohere)
  Human feedback plays a central role in the alignment of Large Language Models (LLMs).
• BPE Stays on SCRIPT: Structured Encoding for Robust Multilingual Pretokenization (Cohere)
  Byte Pair Encoding (BPE) tokenizers, widely used in Large Language Models, face challenges in multilingual settings, including penalization…
• Block Diffusion: Bridging Autoregressive & Diffusion LMs (Cohere)
  Mar 12, 2025 Block Diffusion: Bridging Autoregressive & Diffusion LMs Authors Marianne Arriola, Aaron Gokaslan, Justin T.
• Intriguing Properties of Compression on Multilingual Models (Cohere)
  Multilingual models are often particularly dependent on scaling to generalize to a growing number of languages.
• The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution (Cohere)
  Humans interpret language using beliefs and prior knowledge about the world. For example, we intuitively understand the response "I wore gl…
• The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AI (Cohere)
  The race to train language models on vast, diverse, and inconsistently documented datasets has raised pressing concerns about the legal and…
• When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs (Cohere)
  Recent advancements in large language models (LLMs) have shifted focus toward scaling inference-time compute, improving performance without…
• Tiny Aya: Bridging Scale and Multilingual Depth (Cohere)
  Tiny Aya redefines what a small multilingual language model can achieve.
• A SMART Mnemonic Sounds like "Glue Tonic": Mixing LLMs with Student Feedback to Make Mnemonic (Cohere)
  Keyword mnemonics are memorable explanations that link new terms to simpler keywords.
• MTEB: Massive Text Embedding Benchmark (Cohere)
  Text embeddings are commonly evaluated on a small set of datasets from a single task not covering their possible applications to other task…
• Predicting Twitter Engagement With Deep Language Models (Cohere)
  Twitter has become one of the main information sharing platforms for millions of users world-wide.
• Mix Data or Merge Models? Optimizing for Diverse Multi-Task Learning (Cohere)
  Large Language Models (LLMs) have been adopted and deployed worldwide for a broad variety of applications.
• Evaluating the Social Impact of Generative AI Systems in Systems and Society (Cohere)
  Generative AI systems across modalities, ranging from text, image, audio, and video, have broad social impacts, but there exists no officia…
• Multilingual Arbitrage: Optimizing Data Pools to Accelerate Multilingual Progress (Cohere)
  The use of synthetic data has played a critical role in recent state-of-art breakthroughs.
• Findings of the WMT25 Multilingual Instruction Shared Task: Persistent Hurdles in Reasoning (Cohere)
  The WMT25 Multilingual Instruction Shared Task (MIST) introduces a benchmark to evaluate large language models (LLMs) across 30 languages.
• Which Prompts Make The Difference? Data Prioritization For Efficient Human LLM Evaluation (Cohere)
  Data Prioritization For Efficient Human LLM Evaluation Human evaluation of LLMs is critical, but comes at a high cost.
• LLM2Vec-Gen: Generative Embeddings from Large Language Models (Cohere)
  LLM2 Vec-Gen: Generative Embeddings from Large Language Models Fine-tuning LLM-based text embedders via contrastive learning maps inputs an…
• Command A: An Enterprise-Ready Large Language Model (Cohere)
  In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise us…
• On the Fairness Impacts of Hardware Selection in Machine Learning (Cohere)
  In the machine learning ecosystem, hardware selection is often regarded as a mere utility, overshadowed by the spotlight on algorithms and…
• Studying the Impact of Magnitude Pruning on Contrastive Learning Methods (Cohere)
  We study the impact of different pruning techniques on the representation learned by deep neural networks trained with contrastive loss fun…
• Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning (Cohere)
  Datasets are foundational to many breakthroughs in modern artificial intelligence.
• Mitigating Harm in Language Models with Conditional-Likelihood Filtration (Cohere)
  Nov 28, 2021 Mitigating Harm in Language Models with Conditional-Likelihood Filtration Authors Helen Ngo, Cooper Raterink, João G.M.
• Commit0: Library Generation from Scratch (Cohere)
  With the goal of benchmarking generative systems beyond expert software development ability, we introduce Commit0, a benchmark that challen…
• Unlocking Reasoning Capability on Machine Translation in Large Language Models (Cohere)
  Reasoning-oriented large language models (RLMs) achieve strong gains on tasks such as mathematics and coding by generating explicit interme…
• Reverse Engineering Human Preferences with Reinforcement Learning (Cohere)
  The capabilities of Large Language Models (LLMs) are routinely evaluated by other LLMs trained to predict human preferences.
• M-RewardBench: Evaluating Reward Models in Multilingual Settings (Cohere)
  Reward models (RMs) have driven the state-of-the-art performance of LLMs today by enabling the integration of human feedback into the langu…