5 papers
Shepherd: Enabling Programmable Meta-Agents via Reversible Agentic Execution Traces
Simon Yu, Derek Chong, Ananjan Nandi +4
As LLM agent systems take on more complex tasks, they increasingly rely on meta-agents: higher-order agents that create, operate on and manage other agents. Meta-agent operations s…
CTC-DRO: Robust Optimization for Reducing Language Disparities in Speech Recognition
Martijn Bartelds, Ananjan Nandi, Moussa Koulako Bala Doumbouya +3
Modern deep learning models often achieve high overall performance, but consistently fail on specific subgroups. Group distributionally robust optimization (group DRO) addresses th…
RL-Guided Data Selection for Language Model Finetuning
Animesh Jha, Harshit Gupta, Ananjan Nandi
Data selection for finetuning Large Language Models (LLMs) can be framed as a budget-constrained optimization problem: maximizing a model's downstream performance under a strict tr…
h4rm3l: A language for Composable Jailbreak Attack Synthesis
Moussa Koulako Bala Doumbouya, Ananjan Nandi, Gabriel Poesia +5
Despite their demonstrated valuable capabilities, state-of-the-art (SOTA) widely deployed large language models (LLMs) still have the potential to cause harm to society due to the…
Sneaking Syntax into Transformer Language Models with Tree Regularization
Ananjan Nandi, Christopher D. Manning, Shikhar Murty
While compositional accounts of human language understanding are based on a hierarchical tree-like process, neural models like transformers lack a direct inductive bias for such tr…