5 papers
Causal Intervention-Based Memory Selection for Long-Horizon LLM Agents
Saksham Sahai Srivastava
Long-horizon LLM agents rely on persistent memory to support interactions across sessions, yet existing memory systems often retrieve context using semantic similarity or broad his…
MemoryGraft: Persistent Compromise of LLM Agents via Poisoned Experience Retrieval
Saksham Sahai Srivastava, Haoyu He
Large Language Model (LLM) agents increasingly rely on long-term memory and Retrieval-Augmented Generation (RAG) to persist experiences and refine future performance. While this ex…
A Technical Survey of Reinforcement Learning Techniques for Large Language Models
Saksham Sahai Srivastava, Vaneet Aggarwal
This survey offers a comprehensive foundation on the integration of RL with language models, highlighting prominent algorithms such as Proximal Policy Optimization (PPO), Q-Learnin…
MathDivide: Improved mathematical reasoning by large language models
Saksham Sahai Srivastava, Ashutosh Gandhi
Large language models have been proven to be capable of handling complex linguistic and cognitive tasks. Therefore their usage has been extended to tasks requiring logical reasonin…
Effective Fault Localization using Probabilistic and Grouping Approach
Saksham Sahai Srivastava, Arpita Dutta, Rajib Mall
Context: Fault localization (FL) is the key activity while debugging a program. Any improvement to this activity leads to significant improvement in total software development cost…