57 citations · 67 across the 10 of their papers we have counts for
7 papers · 1 filter
RLPE: Teaching LLMs to Prompt with Reinforcement Learning
Rahul Singhal, Karime Maamari, Pradyumna Tambwekar
Prompting is a widely used method for adapting general-purpose LLMs to domain-specific tasks. Effective prompts can be tedious to create manually, so prompt writing is increasingly…
AgentMemGate: Addressing Speculation Contamination in Conversational Assistant Memory
Chirag Sharma, Benjamin Fowlersmith, Karime Maamari
Conversational AI assistants with long-term memory extract facts from user messages into a store consulted in later conversations. A stated plan can enter that store as fact: a use…
HARDEN: Constrained Evolutionary Search for Harder, Answer-Preserving Evaluation Cases
Aditya Kumaran, Rahul Singhal, Karime Maamari +2
Language models are often evaluated on curated benchmarks that underrepresent the complexity of enterprise deployments. We introduce HARDEN, a constrained evolutionary search metho…
Environment Maps: Structured Environmental Representations for Long-Horizon Agents
Yenchia Feng, Chirag Sharma, Karime Maamari
Although large language models (LLMs) have advanced rapidly, robust automation of complex software workflows remains an open problem. In long-horizon settings, agents frequently su…
Lattice: Generative Guardrails for Conversational Agents
Emily Broadhurst, Tawab Safi, Joseph Edell +2
Conversational AI systems require guardrails to prevent harmful outputs, yet existing approaches use static rules that cannot adapt to new threats or deployment contexts. We introd…
How Many Instructions Can LLMs Follow at Once?
Daniel Jaroslawicz, Brendan Whiting, Parth Shah +1
Production-grade LLM systems require robust adherence to dozens or even hundreds of instructions simultaneously. However, the instruction-following capabilities of LLMs at high ins…
GenEdit: Compounding Operators and Continuous Improvement to Tackle Text-to-SQL in the Enterprise
Karime Maamari, Connor Landy, Amine Mhedhbi
Recent advancements in Text-to-SQL, driven by large language models, are democratizing data access. Despite these advancements, enterprise deployments remain challenging due to the…