Large language models

Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.

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arXiv AI

Jun 24

RAVEN: A Regime-Aware Variable-context Expert Network for Financial Time Series Forecasting

arXiv:2606. 24062v1 Announce Type: cross Abstract: Financial time series forecasting presents structural challenges absent from standard benchmarks.

By Cheng He, Zhenyu Guan, Xijie Liang, Defu Lian, Jiajia Li, Enhong Chen, Patrick P. C. Lee, Geng Hu, Zehao Chen

llms benchmarks

arXiv Machine Learning

Jun 24

Polaris: A Godel Agent Framework for Small Language Models through Experience-Abstracted Policy Repair

arXiv:2603. 23129v3 Announce Type: replace Abstract: G\"odel agent realize recursive self-improvement: an agent inspects its own policy and traces and then modifies that policy in a tested loop.

By Aditya Kakade, Vivek Srivastava, Shirish Karande

llms agents benchmarks

arXiv Machine Learning

Jun 24

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training

arXiv:2602. 21321v2 Announce Type: replace Abstract: Analog in-memory computing (AIMC) performs computation directly within resistive crossbar arrays, offering an energy-efficient platform to scale large vision and language models.

By Quan Xiao, Jindan Li, Zhaoxian Wu, Tayfun Gokmen, Tianyi Chen

llms safety

arXiv AI

Jun 24

A specialized reasoning large language model for accelerating rare disease diagnosis: a randomized AI physician assistance trial

arXiv:2606. 24510v1 Announce Type: new Abstract: Rare diseases affect millions of individuals worldwide, yet timely diagnosis remains a major public health challenge due to scarcity of specialized clinical expertise.

By Haichao Chen, Songchi Zhou, Zhengyun Zhao, Shikai Hu, Xianghong Jin, Hongwei Ji, Li He, Shuli Li, Yiming Qin, Xin Tan, Runfeng Shi, Yih Chung Tham, Jiaye Zhu, Ye Li, Ye Jin, Longhao Cao, Dawei Li, Honghan Wu, Hongqiu Gu, Guanqiao Li, Tudor Groza, Chunying Li, Dian Zeng, Weihong Yu, Gareth Baynam, Saumya Shekhar Jamuar, Min Shen, Shuyang Zhang, Bin Sheng, Sheng Yu, Tien Yin Wong

llms benchmarks

arXiv Machine Learning

Jun 24

Forget Without Compromise: Nexus Sampling for Streaming KV-Cache Eviction Under Fixed Budgets

arXiv:2606. 23961v1 Announce Type: new Abstract: Long-context and agentic LLM workloads push the KV cache past any fixed memory budget, forcing the inference stack to permanently evict tokens at every step of a continuous-inference stream.

By Duc Duong, Hoang Anh Duy Le, Jianwen Xie, Anshumali Shrivastava, Zhaozhuo Xu

llms agents efficiency

arXiv AI

Jun 24

Grading the Grader: Lessons from Evaluating an Agentic Data Analysis System

arXiv:2606. 24839v1 Announce Type: new Abstract: Agentic data analysis systems produce rich outputs, including code, numerical results, and verbal diagnostics.

By Tian Zheng, Kai-Tai Hsu

llms agents

arXiv AI

Jun 24

LaGO: Latent Action Guidance for Online Reinforcement Learning

arXiv:2606. 24669v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for planning and sequential decision-making, but prior work often relies on using them as direct controllers, which requires precise action generation and can be unreliable in practice.

By Kuan-Yen Liu, Ren-Jyun Huang, Ti-Rong Wu

llms reinforcement-learning robotics benchmarks

arXiv Machine Learning

Jun 24

Reasoning as Attractor Dynamics: Latent Memory Retrieval via Gibbs-Weighted Energy Minimization

arXiv:2606. 24543v1 Announce Type: new Abstract: Large Language Models (LLMs) are traditionally viewed as autoregressive generators.

By Kanishk Awadhiya

llms safety

arXiv Machine Learning

Jun 24

Harmonic: Hierarchical State Space Models for Efficient Long-Context Language Modeling

arXiv:2606. 24650v1 Announce Type: cross Abstract: We present Harmonic, a hierarchical state space model (SSM) for language modeling.

By Petr Nyoma

llms benchmarks

arXiv AI

Jun 24

On the Stability of Prompt Ranking in Large Language Model Evaluation

arXiv:2606. 24381v1 Announce Type: cross Abstract: Prompt-based interaction has become a dominant paradigm for using large language models (LLMs), where multiple candidate prompts are evaluated and the top-ranked one is selected for downstream use.

By Shaoshuai Du, Penghao Liang, Yixian Shen, Chuanqi Shi, Hang Zhang, Lun Wang

llms benchmarks

arXiv AI

Jun 24

Agon: An Autonomous Large-Scale Omnidisciplinary Research System Built on Prompt Economy

arXiv:2606. 24177v1 Announce Type: cross Abstract: Large language models are making research production scalable, shifting the bottleneck from producing artifacts to judging claims.

By Youran Sun, Xingyu Ren, Chugang Yi, Jiaxuan Guo, Kejia Zhang, Jianda Du, Haizhao Yang

llms agents

arXiv AI

Jun 24

MedPCFM: Improving Medical Point Cloud Completion by Integrating Point Transformers and Flow Matching

arXiv:2606. 24433v1 Announce Type: cross Abstract: Medical point cloud completion is important for anatomical reconstruction and downstream clinical workflows, yet generative modeling in this setting remains insufficiently studied.

By Kamil Kwarciak, Marek Wodzinski

llms diffusion efficiency benchmarks

arXiv AI

Jun 24

Mind the Heads: Topological Representation Alignment for Multimodal LLMs

arXiv:2606. 23885v1 Announce Type: cross Abstract: Representation alignment has emerged as an effective approach to improve Multimodal Large Language Models (MLLMs) by regularizing their internal representations toward those of an external vision encoder.

By Davide Caffagni, Alberto Compagnoni, Federico Melis, Sara Sarto, Pier Luigi Dovesi, Mark Granroth-Wilding, Marcella Cornia, Lorenzo Baraldi

llms multimodal benchmarks safety

arXiv AI

Jun 24

OpenThoughts-Agent: Data Recipes for Agentic Models

arXiv:2606. 24855v1 Announce Type: new Abstract: Agentic language models dramatically expand the applications of AI yet little is publicly known about how to curate training data for broadly capable agents.

By Negin Raoof, Richard Zhuang, Marianna Nezhurina, Etash Guha, Atula Tejaswi, Ryan Marten, Charlie F. Ruan, Tyler Griggs, Alexander Glenn Shaw, Hritik Bansal, E. Kelly Buchanan, Artem Gazizov, Reinhard Heckel, Chinmay Hegde, Sankalp Jajee, Daanish Khazi, Emmanouil Koukoumidis, Xiangyi Li, Hange Liu, Shlok Natarajan, Harsh Raj, Nicholas Roberts, Ethan Shen, Nishad Singhi, Michael Siu, Ashima Suvarna, Hanwen Xing, Patrick Yubeaton, Robert Zhang, Leon Liangyu Chen, Xiaokun Chen, Steven Dillmann, Saadia Gabriel, Xunyi Jiang, Anurag Kashyap, Boxuan Li, Yein Park, Minh Pham, Sujay Sanghavi, Lin Shi, Ke Sun, Yixin Wang, Zhiwei Xu, Erica Zhang, Siyan Zhao, Wanjia Zhao, Jenia Jitsev, Alex Dimakis, Benjamin Feuer, Ludwig Schmidt

llms agents fine-tuning benchmarks data-engineering

arXiv AI

Jun 24

Beyond Trajectory Imitation: Strategy-Guided Policy Optimization for LLM Reasoning

arXiv:2606. 24064v1 Announce Type: new Abstract: Distilling reasoning capabilities from strong to weak language models typically involves imitating specific solution trajectories, effectively transferring what to answer rather than how to reason.

By Tianyuan Shi, Canbin Huang, Bei Li, Xin Chen, Xiaojun Quan, Jingang Wang, Qifan Wang

llms agents reinforcement-learning fine-tuning efficiency benchmarks

arXiv AI

Jun 24

Governed Shared Memory for Multi-Agent LLM Systems

arXiv:2606. 24535v1 Announce Type: new Abstract: Multi-agent LLM environments require robust mechanisms for shared knowledge management.

By Yanki Margalit, Nurit Cohen-Inger, Erni Avram, Ran Taig, Oded Margalit

llms agents

arXiv AI

Jun 24

Reinforcement Learning Towards Broadly and Persistently Beneficial Models

arXiv:2606. 24014v1 Announce Type: new Abstract: As AI systems are deployed across increasingly diverse and high-stakes settings, model alignment must generalize beyond the tasks and domains seen during training.

By Akshay V. Jagadeesh, Rahul K. Arora, Khaled Saab, Ali Malik, Mikhail Trofimov, Foivos Tsimpourlas, Johannes Heidecke, Karan Singhal

llms reinforcement-learning fine-tuning benchmarks safety

arXiv AI

Jun 24

Deciphering Fingerprints of 3D Molecular Surfaces for Accurate Epitope Prediction

arXiv:2606. 23830v1 Announce Type: cross Abstract: Molecular surfaces encode the geometric and physicochemical patterns that determine antibody-antigen recognition, central to epitope prediction.

By Fang Wu, Weihao Xuan, Jure Leskovec, Yejin Choi, Li Erran Li

llms benchmarks

arXiv Machine Learning

Jun 24

Not All Invariants Are Equal: Curating Training Data to Accelerate Program Verification with SLMs

arXiv:2603. 15510v2 Announce Type: replace Abstract: The synthesis of inductive loop invariants remains a critical bottleneck in automated program verification.

By Ido Pinto, Yizhak Yisrael Elboher, Haoze Wu, Nina Narodytska, Guy Katz

llms fine-tuning

arXiv AI

Jun 24

When Helpfulness Overrides Causal Caution: Context-Dependent Suppression and Recovery in LLMs

arXiv:2606. 24370v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into decision-support roles in business and policy contexts.

By Hiroshi Okumura

llms agents benchmarks

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