3 citations · 3 across the 2 of their papers we have counts for
3 papers
Less Context, Better Agents: Efficient Context Engineering for Long-Horizon Tool-Using LLM Agents
Abhilasha Lodha, Mahsa Pahlavikhah Varnosfaderani, Abir Chakraborty +1
Large language models deployed as autonomous agents for enterprise workflows face a key challenge: verbose tool responses from enterprise systems can cause context overflow, stale-…
Multi-hop Question Answering over Knowledge Graphs using Large Language Models
Abir Chakraborty
Knowledge graphs (KGs) are large datasets with specific structures representing large knowledge bases (KB) where each node represents a key entity and relations amongst them are ty…
The RL/LLM Taxonomy Tree: Reviewing Synergies Between Reinforcement Learning and Large Language Models
Moschoula Pternea, Prerna Singh, Abir Chakraborty +4
In this work, we review research studies that combine Reinforcement Learning (RL) and Large Language Models (LLMs), two areas that owe their momentum to the development of deep neu…