Sarath Chandar

2 papers indexed

arxivcs.CLcs.AI2026-07-04

Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language

Diego Cerda-Mardini, Sarath Chandar, Sreenath Madathil

LLMs are increasingly deployed as post-hoc explainers of AI-generated outputs, yet it remains unclear whether they can reliably communicate probabilistic information in natural language. For this role to be viable, models must produce identical verbal descriptions for identical i…

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arxivcs.LGcs.AI2026-07-01

Loss Smoothing for Stable Adaptation Under Distribution Shift

Darshan Patil, Ekaterina Lobacheva, Razvan Pascanu, Sarath Chandar

In settings such as fine-tuning and reinforcement learning, neural networks are often adapted under distribution shift. Standard adaptation methods typically optimize the target objective directly, inducing an abrupt change from the source training objective. This abrupt transiti…

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