12 citations · 12 across the 8 of their papers we have counts for
4 papers · 1 filter
Memory as Middleware for Self-Improving AI Agents
K. R. Jayaram, Vatche Isahagian, Vinod Muthusamy +4
AI agents are stateless across sessions by default and therefore operationally amnesic: each session begins with little durable knowledge of prior failures, repairs, preferences, o…
The Hard Decision Layer: Evidence for Committed Inference in Transformers
Ashwath Vaithinathan Aravindan, Mayank Kejriwal
We investigate where and how transformer-based language models commit to predictions in multiple-choice question answering. We identify the _Hard Decision Layer_ (HDL), a natural a…
Second Guess: Detecting Uncertainty Through Abstention and Answer Stability in Small Language Models
Ashwath Vaithinathan Aravindan, Mayank Kejriwal
Large language models often generate confident but incorrect answers rather than abstaining when uncertain. This problem is particularly acute for small language models (SLMs), whe…
Code-Driven Planning in Grid Worlds with Large Language Models
Ashwath Vaithinathan Aravindan, Zhisheng Tang, Mayank Kejriwal
We propose an iterative programmatic planning (IPP) framework for solving grid-based tasks by synthesizing interpretable agent policies expressed in code using large language model…