Antoine Déchappe
About me
Latest research review
Why do multi-agent systems fail?
Mar 25, 2025
Recent writing
Beware of poetry package named differently from project structure
Mar 27, 2025
Pre-commit options in pyproject.toml should be committed first
Mar 12, 2025
Build a chess dataset from PGNs
Feb 25, 2025
Antoine Déchappe
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Research review
Deep Learning
Averaging weights leads to wider optima and better generalization
Distilling the knowledge in a neural network
Effect of the initial configuration of weights on the training and function of artificial neural networks
LLMs
Agents
Why do multi-agent systems fail?
Benchmarks
τ -bench Benchmark for Tool-Agent-User Interaction in Real-World Domains
Privacy
Does your LLM truly unlearn ? An embarrassingly simple approach to recover unlearned knowledge
LLMs can infer and verbalize latent structure from disparate training data
Reasoning
Coconut: Continuous latent space reasoning for language models
Imagine while reasoning in space: Multimodal Visualization-of-Thought
Structured outputs
Automata-based constraints for language model decoding
Training
Branch-Train-Merge: embarrassingly parallel training of expert Language Models
Smaller, weaker, yet better: training LLM reasoners via compute-optimal sampling
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