18 citations · 18 across the 3 of their papers we have counts for
4 papers · 1 filter
Forecasting Downstream Performance of LLMs With Proxy Metrics
Arkil Patel, Siva Reddy, Marius Mosbach +1
Progress in language model development is often driven by comparative decisions: which architecture to adopt, which pretraining corpus to use, or which training recipe to apply. Ma…
DeepSeek-R1 Thoughtology: Let's think about LLM Reasoning
Sara Vera MarjanoviÄ, Arkil Patel, Vaibhav Adlakha +14
Large Reasoning Models like DeepSeek-R1 mark a fundamental shift in how LLMs approach complex problems. Instead of directly producing an answer for a given input, DeepSeek-R1 creat…
Investigating Adversarial Trigger Transfer in Large Language Models
Nicholas Meade, Arkil Patel, Siva Reddy
Recent work has developed optimization procedures to find token sequences, called adversarial triggers, which can elicit unsafe responses from aligned language models. These trigge…
How to Get Your LLM to Generate Challenging Problems for Evaluation
Arkil Patel, Siva Reddy, Dzmitry Bahdanau
The pace of evolution of Large Language Models (LLMs) necessitates new approaches for rigorous and comprehensive evaluation. Traditional human annotation is increasingly impractica…