7 citations · 25 across the 18 of their papers we have counts for
20 papers
Physics of Agents: Statistical Mechanics Predicts Collective Behavior of AI Agents
Batu El, Jinhee Paeng, Fatih Dinc +7
AI agents increasingly operate as part of interacting systems rather than in isolation. As agents exchange information and jointly make decisions, their interactions can improve co…
Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing
Jiacheng Miao, Jin Mu, Guanhua Chen +1
Reliable hypothesis testing is the foundation of many empirical scientific claims. Large language model (LLM) agents are increasingly used to automate this process, as they can ins…
The Agentic Garden of Forking Paths
Jiacheng Miao, Jonathan K Pritchard, James Zou
Empirical research rarely admits a unique analysis. Different analytical choices can lead to different conclusions from the same data, yet these hidden forking paths are difficult…
What LLMs Think When You Don't Tell Them What to Think About?
Yongchan Kwon, James Zou
Characterizing the behavior of large language models (LLMs) across diverse settings is critical for reliable monitoring and AI safety. However, most existing analyses rely on topic…
Multi-Agent Teams Hold Experts Back
Aneesh Pappu, Batu El, Hancheng Cao +4
Multi-agent LLM systems are increasingly deployed as autonomous collaborators, where agents interact freely rather than execute fixed, pre-specified workflows. In such settings, ef…
Sparse Reward Subsystem in Large Language Models
Guowei Xu, Mert Yuksekgonul, James Zou
Recent studies show that LLM hidden states encode reward-related information, such as answer correctness and model confidence. However, existing approaches typically fit black-box…
A Roadmap for Predictive Human Immunology
Aly A. Khan, Jason Perera, James Zou +13
For over a century, immunology has masterfully discovered and dissected the components of our immune system, yet its collective behavior remains fundamentally unpredictable. In thi…
Paper2Agent: Reimagining Research Papers As Interactive and Reliable AI Agents
Jiacheng Miao, Joe R. Davis, Yaohui Zhang +2
We introduce Paper2Agent, an automated framework that converts research papers into AI agents. Paper2Agent transforms research output from passive artifacts into active systems tha…
Inefficiencies of Meta Agents for Agent Design
Batu El, Mert Yuksekgonul, James Zou
Recent works began to automate the design of agentic systems using meta-agents that propose and iteratively refine new agent architectures. In this paper, we examine three key chal…
Moloch's Bargain: Emergent Misalignment When LLMs Compete for Audiences
Batu El, James Zou
Large language models (LLMs) are increasingly shaping how information is created and disseminated, from companies using them to craft persuasive advertisements, to election campaig…
Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Qizheng Zhang, Changran Hu, Shubhangi Upasani +10
Large language model (LLM) applications such as agents and domain-specific reasoning increasingly rely on context adaptation: modifying inputs with instructions, strategies, or evi…
ACT: Agentic Classification Tree
Vincent Grari, Tim Arni, Thibault Laugel +3
When used in high-stakes settings, AI systems are expected to produce decisions that are transparent, interpretable and auditable, a requirement increasingly expected by regulation…
4KAgent: Agentic Any Image to 4K Super-Resolution
Yushen Zuo, Qi Zheng, Mingyang Wu +10
We present 4KAgent, a unified agentic super-resolution generalist system designed to universally upscale any image to 4K resolution (and even higher, if applied iteratively). Our s…
metaTextGrad: Automatically optimizing language model optimizers
Guowei Xu, Mert Yuksekgonul, Carlos Guestrin +1
Large language models (LLMs) are increasingly used in learning algorithms, evaluations, and optimization tasks. Recent studies have shown that using LLM-based optimizers to automat…
Can LLM feedback enhance review quality? A randomized study of 20K reviews at ICLR 2025
Nitya Thakkar, Mert Yuksekgonul, Jake Silberg +6
Peer review at AI conferences is stressed by rapidly rising submission volumes, leading to deteriorating review quality and increased author dissatisfaction. To address these issue…
Cost-of-Pass: An Economic Framework for Evaluating Language Models
Mehmet Hamza Erol, Batu El, Mirac Suzgun +2
Widespread adoption of AI systems hinges on their ability to generate economic value that outweighs their inference costs. Evaluating this tradeoff requires metrics accounting for…
Science Across Languages: Assessing LLM Multilingual Translation of Scientific Papers
Hannah Calzi Kleidermacher, James Zou
Scientific research is inherently global. However, the vast majority of academic journals are published exclusively in English, creating barriers for non-native-English-speaking re…
Optimizing Calibration by Gaining Aware of Prediction Correctness
Yuchi Liu, Lei Wang, Yuli Zou +2
Model calibration aims to align confidence with prediction correctness. The Cross-Entropy (CE) loss is widely used for calibrator training, which enforces the model to increase con…
The complementary contributions of academia and industry to AI research
Lizhen Liang, Han Zhuang, James Zou +1
Artificial intelligence (AI) has seen fast paced development in industry and academia. However, striking recent advances by industry have stunned the field, inviting a fresh perspe…
New Evaluation Metrics Capture Quality Degradation due to LLM Watermarking
Karanpartap Singh, James Zou
With the increasing use of large-language models (LLMs) like ChatGPT, watermarking has emerged as a promising approach for tracing machine-generated content. However, research on L…