1 citations · 1 across the 2 of their papers we have counts for
3 papers
Training Advisors for LLM Agents from Task Outcomes
Sergei Polezhaev, Barys Liskavets, Ori Press +1
Large language model agents tackle multi-step tasks by interleaving reasoning and tool calls with observations from the environment. Prior work has shown that natural-language feed…
Task-agnostic Prompt Compression with Context-aware Sentence Embedding and Reward-guided Task Descriptor
Barys Liskavets, Shuvendu Roy, Maxim Ushakov +3
The rise of Large Language Models (LLMs) has led to significant interest in prompt compression, a technique aimed at reducing the length of input prompts while preserving critical…
Prompt Compression with Context-Aware Sentence Encoding for Fast and Improved LLM Inference
Barys Liskavets, Maxim Ushakov, Shuvendu Roy +3
Large language models (LLMs) have triggered a new stream of research focusing on compressing the context length to reduce the computational cost while ensuring the retention of hel…