3 citations · 4 across the 6 of their papers we have counts for
7 papers
Dream-RSI: Recursive Self-Improvement through Evolving Worlds
Tong Zheng, Xidong Wu, Zheng Zhang +14
Recursive self-improvement is becoming essential for autonomous AI agents, whose progress depends on discovering high-value solutions across complex domains. Effective exploration…
Gemma 4 Technical Report
Gemma Team, Sherif El Abd, Vaibhav Aggarwal +320
We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemm…
PACEvolve++: Improving Test-time Learning for Evolutionary Search Agents
Minghao Yan, Bo Peng, Benjamin Coleman +11
Large language models have become drivers of evolutionary search, but most systems rely on a fixed, prompt-elicited policy to sample next candidates. This limits adaptation in prac…
AgenticTagger: Structured Item Representation for Recommendation with LLM Agents
Zhouhang Xie, Bo Peng, Zhankui He +11
High-quality representations are a core requirement for effective recommendation. In this work, we study the problem of LLM-based descriptor generation, i.e., keyphrase-like natura…
PACEvolve: Enabling Progress-Aware Consistent Evolution
Minghao Yan, Bo Peng, Benjamin Coleman +13
Self-evolving agents powered by Large Language Models (LLMs) have emerged as a promising direction across diverse domains, including code optimization and scientific discovery, yet…
Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory
Tianxin Wei, Noveen Sachdeva, Benjamin Coleman +12
Statefulness is essential for large language model (LLM) agents to perform long-term planning and problem-solving. This makes memory a critical component, yet its management and ev…
ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation
Yupeng Hou, Jianmo Ni, Zhankui He +5
Generative recommendation (GR) is an emerging paradigm where user actions are tokenized into discrete token patterns and autoregressively generated as predictions. However, existin…