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

StanceBench: A Benchmark for Audio LLM-Based Interpersonal Stance Evaluation from Speech

arXiv:2607. 22658v1 Announce Type: new Abstract: Speech-to-speech dialogue models increasingly depend on prosody and interactional nuance to convey social intent, yet benchmarks for these cues remain limited.

By Yuzhe Wang (Electrical and Computer Engineering Department, Johns Hopkins University, Baltimore, USA), Thomas Thebaud (Electrical and Computer Engineering Department, Johns Hopkins University, Baltimore, USA), Jennifer Hu (Department of Cognitive Science, Johns Hopkins University, Baltimore, USA), Jes\'us Villalba-Lopez (Electrical and Computer Engineering Department, Johns Hopkins University, Baltimore, USA), Venkatesh Ravichandran (Amazon AGI, USA), Georgi Tinchev (Amazon Research, UK), Najim Dehak (Electrical and Computer Engineering Department, Johns Hopkins University, Baltimore, USA), Laureano Moro-Vel\'azquez (Electrical and Computer Engineering Department, Johns Hopkins University, Baltimore, USA)

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arXiv AI

Jul 28

HiLLTS: Zero-Shot Hierarchical LLM-Guided Traffic Signal Control for Sustainable Transportation

arXiv:2607. 22691v1 Announce Type: new Abstract: Urban traffic congestion significantly increases fuel consumption, greenhouse gas emissions, and commuter delays, resulting in substantial economic losses and environmental harm in modern cities.

By Yue Ding, Tendai Mukande, Mingming Liu

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arXiv AI

Jul 28

MPR-CiteG: Enhancing RAG with Multi-Portfolio Retrieval and Citation-Grounded Generation

arXiv:2607. 22706v1 Announce Type: new Abstract: This paper presents the MPR-CiteG framework, which achieved second place in the ScienceON AI Challenge by addressing two fundamental challenges in generative AI: inefficient retrieval and the absence of source verification.

By Hyewon Lee, Minkyung Song, Junghyun Oh, Seunghoon Han, Sungsu Lim

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arXiv AI

Jul 28

TopoFE: topology-aware LLM-guided Automated Feature Engineering

arXiv:2607. 23286v1 Announce Type: new Abstract: Automatic feature engineering (AutoFE) for tabular learning can be naturally formulated as a program synthesis problem, where the objective is to discover predictive feature transformations from an exponentially large search space.

By Sha Li, Naren Ramakrishnan

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arXiv AI

Jul 28

Plato-Bio: verification-first biological novelty screening with temporal rediscovery and structural benchmarks

arXiv:2607. 23975v1 Announce Type: new Abstract: Large language model research agents can connect literature retrieval, analysis code, and manuscript preparation, but coherent output does not establish scientific validity.

By Stefan G. Creadore

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arXiv Machine Learning

Jul 28

Hidden Boundary Motion in Transformer Optimization: Function-Space Orthogonalization of Affine Weight and Bias Updates

arXiv:2607. 22927v1 Announce Type: new Abstract: Weights and biases are normally optimized as separate parameter tensors, yet they do not represent separate functions when the input to an affine layer has nonzero mean.

By Zhang Gongyue, Sheng Yixuan, Liu donghan, Wang Zhiyong, Ren Weihong, Liu honghai

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arXiv AI

Jul 28

Do Diagrams Help Large Language Models Reason? Evidence from Syllogistic Reasoning

arXiv:2607. 23513v1 Announce Type: cross Abstract: Diagrams are widely used to support logical reasoning, and prior studies suggest that representations such as Euler diagrams can improve human reasoning performance.

By Risako Ando, Koji Mineshima

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arXiv AI

Jul 28

CALMRec: Causally Aligned Language Memory for Long-Horizon Recommendation

arXiv:2607. 23647v1 Announce Type: cross Abstract: Large language models (LLMs) can summarize heterogeneous user evidence in natural language, but current LLM recommenders often collapse enduring preferences, transient intent, and exposure-induced behavior into one profile.

By Gengyu Zhan

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arXiv AI

Jul 28

PathScale-R1: Cross-scale Reasoning for Pathological Image Analysis

arXiv:2607. 23794v1 Announce Type: cross Abstract: Pathological diagnosis is inherently multi-scale, requiring the integration of global tissue architecture at low magnification with cellular morphology at higher magnification.

By Chi Phan, Tianyi Zhang, Yufeng Wu, Qiaochu Xue, Jiajie Zhang, Linghan Cai, Zeyu Liu, Sudong Wang, Yueming Jin, Dan Hu

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arXiv AI

Jul 28

Indic DiarBench: A Multilingual Joint Diarization and ASR Benchmark for Indian Languages

arXiv:2607. 23808v1 Announce Type: cross Abstract: In this work, we introduce Indic DiarBench, a speaker diarization and ASR benchmark dataset spanning all 22 scheduled languages of India.

By Deovrat Mehendale, Aditya Mehndiratta, Dhruv Rathi, Kaushal Bhogale, Mitesh M. Khapra

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arXiv AI

Jul 28

DuoAD: Leveraging [CLS] Dual Characteristics for Training-Free Few-Shot Anomaly Detection

arXiv:2607. 23924v1 Announce Type: cross Abstract: Vision foundation models have enabled strong training-free anomaly detection (AD).

By Jyun-Ze Tang, Po-Han Huang, Ming-Ching Chang, Chih-Fan Hsu, Jeng-Lin Li

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arXiv AI

Jul 28

Tag Questions and the Generational Reversal of Sycophancy Across 45 Language Models

arXiv:2607. 23976v1 Announce Type: cross Abstract: Appending a two-word confirmation tag to a decision question -- "Is X the better choice?

By Tapan Parikh

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arXiv Machine Learning

Jul 28

FusionML: Prefill, Not Decode - Mechanism and Boundaries of CPU+GPU Co-Execution on Unified-Memory Apple Silicon

arXiv:2607. 22785v1 Announce Type: cross Abstract: Apple-Silicon SoCs share CPU, GPU, and Neural Engine over one unified memory system, raising the question of whether transformer inference can be accelerated by splitting single operators across units.

By Om Mohite

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arXiv AI

Jul 28

Not Forgotten: Implementation and Evaluation of a Personalized Episodic Memory for the Humanoid Robot Head Kim

arXiv:2607. 24190v1 Announce Type: cross Abstract: Social robots that rely on large language models for conversation are unable to retain information across sessions.

By Steve Aschenbrenner, Marcel Heisler, Thomas Sievers, Christian Becker-Asano

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arXiv AI

Jul 28

Evaluating the Impact of Explainable AI on Trust in AI-Assisted Code Review

arXiv:2607. 24601v1 Announce Type: cross Abstract: Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to understand.

By Zhenhan Gao, Marvin Mu\~noz Bar\'on, Umm-e Habiba, Daniel Graziotin, Stefan Wagner

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arXiv AI

Jul 28

DataOrchestra: Learning to Orchestrate Per-Example Curation of Pretraining Data

arXiv:2607. 24717v1 Announce Type: cross Abstract: Pretraining data processing is critical to the downstream performance of Large Language Models (LLMs).

By Zhen Huang, Yikun Wang, Shijie Xia, Pengfei Liu

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arXiv AI

Jul 28

Bayesian-LoRA: Probabilistic Low-Rank Adaptation of Large Language Models

arXiv:2601. 21003v3 Announce Type: replace Abstract: Large Language Models usually put more emphasis on accuracy and therefore, will guess even when not certain about the prediction, which is especially severe when fine-tuned on small datasets due to the inherent tendency toward miscalibration.

By Moule Lin, Shuhao Guan, Andrea Patane, David Gregg, Goetz Botterweck

llms fine-tuning benchmarks

arXiv AI

Jul 28

From Pixels to Prompts: Vision-Language Models

arXiv:2605. 07544v3 Announce Type: replace Abstract: When you read a paper about a new Vision-Language Model today, it can be easy to forget how strange this idea would have sounded not so long ago.

By Khang Nhat Hoang Vo

llms multimodal benchmarks

arXiv AI

Jul 28

Do LLMs Experience an Internal Polylogue? Investigating Reasoning through the Lens of Personas

arXiv:2605. 09159v2 Announce Type: replace Abstract: Recent work shows that large language models (LLMs) encode behavioral traits ("personas") as linear directions in activation space, often called "persona vectors".

By Nils A. Herrmann, Leander Girrbach, Kirill Bykov, Zeynep Akata

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arXiv Machine Learning

Jul 28

When Low CER is Not Enough: An Analysis of Hallucinations in Vision-Language OCR Systems on Historical Uruguayan Documents

arXiv:2607. 24077v1 Announce Type: cross Abstract: Optical Character Recognition (OCR) is a key component in the digitization of historical archives.

By Marina Gardella (CB), Camilo Mari{\~n}o (UDELAR, CB), Diego Belzarena (UDELAR, CB), Ignacio Ram{\'i}rez (UDELAR), Gregory Randall (UDELAR), Jean-Michel Morel (LU - Hong Kong)

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