papers

Publications (11)

cs.CL2026

Shorthand for Thought: Compressing LLM Reasoning via Entropy-Guided Supertokens

Zhenyu Zhao, Sander Land, Daniel M. Bikel +1

Reasoning in Large Language Models incurs significant inference-time compute, yet the token-level information structure of reasoning traces remains underexplored. We observe that r…

cs.AI2026

Every Eval Ever: A Unifying Schema and Community Repository for AI Evaluation Results

Jan Batzner, Sree Harsha Nelaturu, Damian Stachura +45

AI evaluations are widely used for testing and understanding progress. However, the diverse evaluators bring with them inconsistencies that challenge analysis and comparison. First…

cs.CL2026

Auditing LLM Benchmarks with Item Response Theory

Sander Land, Daniel M. Bikel

LLM benchmark labels are frozen at release and silently propagated into downstream benchmarks, errors and all. We introduce an Item Response Theory-based indicator that surfaces li…

cs.CL2025

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…

cs.CL2024

Fishing for Magikarp: Automatically Detecting Under-trained Tokens in Large Language Models

Sander Land, Max Bartolo

The disconnect between tokenizer creation and model training in language models allows for specific inputs, such as the infamous SolidGoldMagikarp token, to induce unwanted model b…

cs.CL2026

MinGram: A Minimalist Unigram Tokenizer with High Compression and Competitive Morphological Alignment

Sander Land

The Unigram tokenizer uses an elegant representation which makes it straightforward to edit vocabularies, but its training is comparatively heavy and complex. We introduce MinGram…

cs.CL2025

BPE Stays on SCRIPT: Structured Encoding for Robust Multilingual Pretokenization

Sander Land, Catherine Arnett

Byte Pair Encoding (BPE) tokenizers, widely used in Large Language Models, face challenges in multilingual settings, including penalization of non-Western scripts and the creation…

cs.CL2026

Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures

Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377

To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…

cs.CL2026

Which Pieces Does Unigram Tokenization Really Need?

Sander Land, Yuval Pinter

The Unigram tokenization algorithm offers a probabilistic alternative to the greedy heuristics of Byte-Pair Encoding. Despite its theoretical elegance, its implementation in practi…

cs.CL2024

Understanding Likelihood Over-optimisation in Direct Alignment Algorithms

Zhengyan Shi, Sander Land, Acyr Locatelli +2

Direct Alignment Algorithms (DAAs), such as Direct Preference Optimisation (DPO) and Identity Preference Optimisation (IPO), have emerged as alternatives to online Reinforcement Le…

cs.CL2026

RewardBench 2: Advancing Reward Model Evaluation

Saumya Malik, Valentina Pyatkin, Sander Land +4

Reward models are used throughout the post-training of language models to capture nuanced signals from preference data and provide a training target for optimization across instruc…