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

Jul 28

UP-Fuse: Uncertainty-guided LiDAR-Camera Fusion for 3D Panoptic Segmentation

arXiv:2602. 19349v2 Announce Type: replace-cross Abstract: LiDAR-camera fusion enhances 3D panoptic segmentation by leveraging camera images to complement sparse LiDAR scans, but it also introduces a critical failure mode.

By Rohit Mohan, Florian Drews, Yakov Miron, Daniele Cattaneo, Abhinav Valada

llms computer-vision robotics multimodal benchmarks safety

arXiv AI

Jul 28

Lexical discovery in unknown environments orchestrated by Large Language Models

arXiv:2607. 22591v1 Announce Type: new Abstract: Populations of autonomous agents deployed in unknown environments (e.

By Rafael Sendra-Arranz, I\~naki Dellibarda Varela, Eduardo Rocon, \'Alvaro Guti\'errez, Manuel Cebrian

llms rag agents

arXiv AI

Jul 28

How Context Attribution Handles What the Model Already Knows

arXiv:2607. 23804v1 Announce Type: cross Abstract: Context attribution methods for large language models (LLMs) identify which input context contributes to the model response.

By Quoc-Huy Trinh, Lin Zhu, Sebastian Szyller

llms benchmarks

arXiv AI

Jul 28

Evaluating the Impact of Reviewer Guideline Design on LLM-Based Automated Peer Review

arXiv:2607. 22553v1 Announce Type: cross Abstract: Peer review is an essential process in scientific research, yet the growing workload has made its automation increasingly necessary.

By Haowen Li, Yoichi Ishibashi, Masafumi Oyamada

llms

arXiv AI

Jul 28

Evolving from Lessons: Skill-Augmented Table Graph Reasoning for Operation-wise Table Question Answering

arXiv:2607. 22633v1 Announce Type: new Abstract: Table Question Answering (TableQA) aims to reason over tables to answer user queries.

By Guixin Su, Qiankun Pi, Mayi Xu, Wenli Li, Ming Zhong, Yuanyuan Zhu, Jiawei Jiang, Tieyun Qian

llms nlp efficiency

arXiv AI

Jul 28

VlogReward: Learning Multi-Dimensional Evaluation for Vlog Editing

arXiv:2607. 22632v1 Announce Type: new Abstract: The rapid rise of vlogs as a personalized storytelling medium has created a demand for automated systems to evaluate and refine vlog editing plans.

By Yexiang Liu, Wen Zhong, Sijie Zhu, Xin Gu, Fan Chen, Junxian Duan, Jie Cao, Longyin Wen, Zhenfang Chen

llms reinforcement-learning multimodal benchmarks

arXiv AI

Jul 28

CRAFT: Learn the Schema, Execute the Plan

arXiv:2607. 22642v1 Announce Type: new Abstract: Enterprise coding agents translate natural-language analytical requests into executable code over proprietary APIs, schemas, and metric definitions.

By Aakash Kolekar, Sahika Genc, Shahriar Shariat, Bunyamin Sisman, Tibor Mezi, Barbara Poblete, Shree Vandana Kachroo, Calvin Chi, Parth Parmar, Ari Singer, Prayaas Jain, Cindy Barker, Benoit Dumoulin

llms agents reinforcement-learning fine-tuning

arXiv AI

Jul 28

TRACE: Business Rule-Grounded Reasoning Curriculum for Knowledge-Preserving Parametric Tool Retrieval in Enterprise LLMs

arXiv:2607. 22639v1 Announce Type: new Abstract: Parametric retrieval enables LLMs to retrieve tools implicitly by assigning each API a unique virtual token and training the model to generate it via constrained beam search.

By Sai Shruthi Sistla, Ashutosh Hathidara, Christopher Toukmaji, Mayank Shrivastava, Karthikeyan Asokkumar

llms rag fine-tuning

arXiv AI

Jul 28

Extracting Algorithms in Pre-trained LLMs: A Case on Hidden Markov Models

arXiv:2607. 22646v1 Announce Type: new Abstract: Large language models (LLMs) display a striking ability to predict next observations from Hidden Markov Models (HMMs) via in-context learning (ICL), but the algorithm underlying this capability remains undetermined: prior work has proposed several candidates without consensus, and none has been grounded in the model's internal activations.

By Yijia Dai, Zhaolin Gao, Yahya Sattar, Jennifer J. Sun, Sarah Dean

llms

arXiv AI

Jul 28

EventOD: Event-Aware OD Flow Generation via LLM-Guided Semantic Modulation

arXiv:2607. 22655v1 Announce Type: new Abstract: Estimating origin-destination (OD) flows under disruptive events is important for disaster response and urban resilience.

By Jie Zhao, Jie Feng, Can Rong, Zhihan Hou, Peng Lu, Yong Li

llms rag diffusion

arXiv AI

Jul 28

Beyond Block Boundaries: Multi-Block Editing for Diffusion Large Language Models

arXiv:2607. 22663v1 Announce Type: new Abstract: Block diffusion has emerged as the dominant paradigm for scaling discrete diffusion language models (dLLMs), because decoding text in fixed-size blocks preserves parallel generation within each block while keeping the quadratic attention cost tractable.

By Xingyu Mou, Zijin Huang, Tianze Zhang, Yuxin Ma, Lanning Wei, Zengfeng Huang, Da Zheng, Lun Du

llms diffusion fine-tuning efficiency benchmarks

arXiv AI

Jul 28

Beyond Sequential Interaction: Benchmarking Parallel Execution and Coordination for GUI Agents

arXiv:2607. 22689v1 Announce Type: new Abstract: Graphical user interface (GUI) agents are systems powered by large multimodal models (LMMs).

By Zedong Yu, Qianxing Li, Zhi Gao, Liuyu Xiang, Chenrui Shi, Yang Liu, Huiming Wu, Yujie Wei, Yuhao Fei, Yubo Fu, Zhaofeng He

llms agents multimodal benchmarks

arXiv AI

Jul 28

Coordinated Networking for On-Device Agent-Augmented Real-Time Communication

arXiv:2607. 22854v1 Announce Type: new Abstract: AI agents are enabling a new paradigm of agent-augmented real-time communication (RTC), where humans focus on high-level collaboration, while agents autonomously retrieve, analyze, and generate information in real time to support their interactions.

By Goodsol Lee, Juheon Yi, Jinglu Wang, Haowen Xu, Saewoong Bahk, Yan Lu

llms agents safety

arXiv AI

Jul 28

SQBench: A Benchmark for Evaluating Task Delivery by Language-Model Agents in Production-Oriented Workflows

arXiv:2607. 23123v1 Announce Type: new Abstract: Existing evaluations of large language models cover knowledge, reasoning, coding, and tool use, but they rarely treat a verifiable deliverable produced within a constrained workflow as the unit of evaluation.

By Summer Sun (Shaqiu Community)

llms agents benchmarks

arXiv AI

Jul 28

RareLens: Towards End-to-End Rare Disease Care via Aligning Divergent Large Language Model Reasoning

arXiv:2607. 23290v1 Announce Type: new Abstract: Rare diseases collectively affect an estimated 3.

By Xi Chen, Hongru Zhou, Shiyu Feng, Hanyu Zhou, Huahui Yi, Rongsheng Wang, Tiancheng He, Kun Wang, Pingping Liu, Qiankun Li, Sicheng Lin, Huiying Ou, Xiaohong Zheng, Tianying Zang, Zhuohang Wu, Leheng Jiang, Kexin Cao, Wenhan Zhang, ChengYi Li, Zhiyang Wang, Songlin Li, Benyou Wang, Ningbei Yin, Shaoting Zhang, Weili Fu, Jian Li, Kang Li

llms agents

arXiv AI

Jul 28

CAPT: A Multi-task Continuous Autoregressive Transformer enabling Cross-dataset and Cross-species Transfer for Calcium Population Dynamics

arXiv:2607. 23258v1 Announce Type: new Abstract: Large-scale calcium imaging has created an opportunity to build foundation-style models for neural population dynamics, but a central question remains unresolved: \textbf{whether a model pretrained on one collection of recordings can generalize to new datasets, experimental paradigms, and even species.

By Xinhong Xu, Yimeng Zhang, Yuanlong Zhang

llms rag nlp multimodal

arXiv AI

Jul 28

Do LLMs Know Their Vulnerable Scenarios?

arXiv:2607. 23496v1 Announce Type: new Abstract: Safety-aligned large language models are trained to refuse harmful requests, yet embedding the same requests in particular scenarios can bypass their safeguards.

By Ziheng Peng, Huiqi Deng, Haoran Jing, Xuankun Rong, Jiahui Han, Xiting Wang, Na Zou, Xia Hu

llms rag benchmarks safety

arXiv AI

Jul 28

Reality Monitoring in Large Language Models: Self-Knowledge That Transforms with Conversation Memory

arXiv:2607. 23927v1 Announce Type: new Abstract: A conversational AI that cannot tell its own output from what a user said will treat its own mistakes as user-provided facts.

By Saurabh Ranjan, Konstantina Sokratous, Brian Odegaard

llms agents benchmarks safety

arXiv AI

Jul 28

GOTS: Greedy Orthogonal Token Selection for High-Resolution Vision-Language Models

arXiv:2607. 23913v1 Announce Type: new Abstract: Modern vision-language models (VLMs) increasingly rely on dynamic or high-resolution visual encoding, producing thousands of visual tokens that substantially increase downstream language-model inference cost.

By Jun Ling, Tao Huang, Junzhuo Liu, Bowen Tang, Peng Wang

llms multimodal benchmarks

arXiv AI

Jul 28

DICA: Dual-Indicator Guided Contrastive Alignment in Multimodal Large Language Models

arXiv:2607. 23944v1 Announce Type: new Abstract: Human visual reasoning typically follows a coarse-to-fine attention process, starting from global scene understanding and gradually focusing on question-relevant regions.

By Hao Yang, Jin Wang, Xuejie Zhang

llms multimodal benchmarks safety

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