10 citations · 16 across the 8 of their papers we have counts for
12 papers
AIRA_2: Overcoming Bottlenecks in AI Research Agents
Karen Hambardzumyan, Nicolas Baldwin, Edan Toledo +22
Existing research has identified three structural performance bottlenecks in AI research agents: (1) synchronous single-GPU execution constrains sample throughput, limiting the ben…
COvolve: Adversarial Co-Evolution of Large-Language-Model-Generated Policies and Environments via Two-Player Zero-Sum Game
Alkis Sygkounas, Rishi Hazra, Andreas Persson +2
A central challenge in building continually improving agents is that training environments are typically static or manually constructed. This restricts continual learning and gener…
LexiCon: a Benchmark for Planning under Temporal Constraints in Natural Language
Periklis Mantenoglou, Rishi Hazra, Pedro Zuidberg Dos Martires +1
Owing to their reasoning capabilities, large language models (LLMs) have been evaluated on planning tasks described in natural language. However, LLMs have largely been tested on p…
Have Large Language Models Learned to Reason? A Characterization via 3-SAT Phase Transition
Rishi Hazra, Gabriele Venturato, Pedro Zuidberg Dos Martires +1
Large Language Models (LLMs) have been touted as AI models possessing advanced reasoning abilities. In theory, autoregressive LLMs with Chain-of-Thought (CoT) can perform more seri…
Evaluating Efficiency and Engagement in Scripted and LLM-Enhanced Human-Robot Interactions
Tim Schreiter, Jens V. Rüppel, Rishi Hazra +3
To achieve natural and intuitive interaction with people, HRI frameworks combine a wide array of methods for human perception, intention communication, human-aware navigation and c…
Bidirectional Intent Communication: A Role for Large Foundation Models
Tim Schreiter, Rishi Hazra, Jens Rüppel +1
Integrating multimodal foundation models has significantly enhanced autonomous agents' language comprehension, perception, and planning capabilities. However, while existing works…