Search: “models”

SigmaMedStat: Temporal Signal Modeling for ICU False Alarm Reduction

arXiv:2605.29236v1 Announce Type: new Abstract: Alarm fatigue in intensive care units (ICUs) is a well documented patient safety crisis. Clinical monitors generate 350 or more alarms per patient per d

safetyarxiv-cs-lg

29 May 2026

Small Agent Group is the Future of Digital Health

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DGX agent

arXiv:2602.08013v2 Announce Type: replace Abstract: The rapid adoption of large language models (LLMs) in digital health has been driven by a 'scaling-first' philosophy, i.e., the assumption that clin

model-releasesarxiv-cs-ai

29 May 2026

The Trust Paradox: How CS Researchers Engage LLM Leaderboards

arXiv:2605.28966v1 Announce Type: new Abstract: Large language model (LLM) leaderboards rank AI models using standardized benchmarks and have become highly visible across computer science, despite kno

29 May 2026

AdaDPO: Self-Adaptive Direct Preference Optimization with Balanced Gradient Updates

arXiv:2605.28440v1 Announce Type: new Abstract: DPO has become a widely adopted alternative to RLHF for aligning LLMs with human preferences, eliminating the need for a separate reward model or RL loo

AI in SRE: Where and how Google is deploying agentic AI to improve operations

model-releasesgoogle-cloud-ai

Since its inception over 20 years ago, Google has used Site Reliability Engineering (SRE) to keep services like Search, Gmail, Maps, YouTube and Google Cloud reliable and highly available, adhering to

Research

Applications of temporal graph learning for predicting the dynamics of biological systems

arXiv:2605.28659v1 Announce Type: new Abstract: Biological foundation models have shown strong performance in single-cell representation learning by applying transformer architectures directly to gene

researcharxiv-cs-lg

Claude Opus 4.8: 'a modest but tangible improvement'

model-releasessimon-willison

Anthropic shipped Claude Opus 4.8 today. My favourite thing about it is this note in the release announcement: Users will find Opus 4.8 to be a modest but tangible improvement on its predecessor. Ther

DebFilter: Eradicating Biases Stashed in Value

arXiv:2605.28167v1 Announce Type: new Abstract: Text-to-image diffusion models, which are theoretically equivalent to score-based generative models, generate images through a multi-step denoising proc

safetyarxiv-cs-cv

FPMoE: A Sparse Mixture-of-Experts Approach to Functional Code Generation

arXiv:2605.27849v1 Announce Type: cross Abstract: Despite rapid progress in LLM-based code generation, existing models are predominantly trained on imperative languages, leaving functional programming

Heterogeneous Multi-Agent Modeling for Measurement and Network Analysis of the Data Service Market

arXiv:2605.27433v1 Announce Type: cross Abstract: With the increasing complexity of collaboration among various social entities and user demands, the factors affecting the stable development of the da

agentsarxiv-cs-ai

KVoiceBench, KOpenAudioBench, and KMMAU: Agent-Driven Korean Speech Benchmarks for Evaluating SpeechLMs

arXiv:2605.27984v1 Announce Type: cross Abstract: Speech language models (SpeechLMs) have achieved substantial progress by extending large language models (LLMs) to the speech modality. However, Speec

Mathematical Modelling of Ethical AI Use in Higher Education: A Coordination Game Framework for Future-Facing Learning

arXiv:2605.27400v1 Announce Type: cross Abstract: The rapid uptake of generative artificial intelligence (AI) in higher education is reshaping assessment practices and intensifying concerns around aca

safetyarxiv-cs-ai

Applications

Measuring Massive Multitask Chinese Understanding

arXiv:2304.12986v3 Announce Type: replace-cross Abstract: The development of large-scale Chinese language models is flourishing, yet there is a lack of corresponding capability assessments. Therefore,

applicationsarxiv-cs-ai

MTAVG-Bench 2.0: Diagnosing Failure Modes of Cinematic Expressiveness in Multi-Talker Audio-Video Generation

arXiv:2605.28035v1 Announce Type: new Abstract: In recent years, Multi-Talker Audio-Video Generation (MTAVG) models have shown promising performance on fundamental metrics such as lip-sync and audio-v

Multi-Adapter Representation Interventions via Energy Calibration

arXiv:2605.28722v1 Announce Type: new Abstract: Representation intervention has emerged as a promising paradigm for aligning large language models toward desired behaviors without modifying model weig

MUSE: Benchmarking Manufacturable, Functional, and Assemblable Text-to-CAD Generation

arXiv:2605.28579v1 Announce Type: new Abstract: Large language models (LLMs) have recently advanced text-driven 3D generation, yet Text-to-CAD remains far from supporting industrial product design. Ex

The Alignment Floor: When Persona Customization Is Safe

arXiv:2605.27382v1 Announce Type: cross Abstract: A key promise of pluralistic AI is behavioral adaptation: persona prompts like 'be creative' or 'be thorough' let systems respect diverse user values

TRACES: Proactive Safety Auditing for Multi-Turn LLM Agents via Trajectory-State Modeling

arXiv:2605.27690v1 Announce Type: new Abstract: LLM agents increasingly operate through multi-turn tool use and environment interaction, where safety risks often emerge from intermediate steps long be

safetyarxiv-cs-cl

ADRD-Bench: A Preliminary LLM Benchmark for Alzheimer's Disease and Related Dementias

arXiv:2602.11460v2 Announce Type: replace Abstract: Large language models (LLMs) have shown great potential for healthcare applications. However, existing evaluation benchmarks provide minimal coverag

Benchmark Leakage Trap: Can We Trust LLM-based Recommendation?

arXiv:2602.13626v3 Announce Type: replace Abstract: The expanding integration of Large Language Models (LLMs) into recommender systems poses critical challenges to evaluation reliability. This paper i

Constraint acquisition needs better benchmarks

arXiv:2605.26279v1 Announce Type: new Abstract: Constraint Acquisition (CA) and related research on the validation and enhancement of Mathematical Programming (MP) models from domain knowledge artifac

DunbaaBERT: From Sacrifice to Semantics

arXiv:2605.26935v1 Announce Type: new Abstract: Large language models have achieved strong performance across many NLP tasks, yet Urdu remains comparatively underexplored due to limited resources and

EmoDistill: Offline Emotion Skill Distillation for Language Model Agents in Adversarial Negotiation

arXiv:2605.26785v1 Announce Type: cross Abstract: Post-trained LLMs are often optimized to align responses with human preferences, making them safe, polite, and conversationally appropriate. In advers

safetyarxiv-cs-ai

Geometry-Aware Representation Denoising for Robust Multi-view 3D Reconstruction

model-releasesarxiv-cs-cv

arXiv:2605.26230v1 Announce Type: new Abstract: Multi-view 3D reconstruction has achieved remarkable progress with the advent of feed-forward 3D reconstruction models. However, these models are typica

I think Anthropic and OpenAI have found product-market fit

model-releasessimon-willison

Anthropic are strongly rumored to be about to have their first profitable quarter. Stories are circulating of companies surprised at how expensive their LLM bills are becoming from usage by their staf

MTL-FNO: A Lightweight Multi-Task Fourier Neural Operator for Sparse Field Reconstruction

arXiv:2605.26718v1 Announce Type: new Abstract: Efficient onboard multi-field sparse reconstruction is essential for the autonomous operation of aerospace vehicles. While existing deep learning models

Prompt Injection Detection is Regime-Dependent: A Deployment-Aware Evaluation with Interpretable Structural Signals

arXiv:2605.26999v1 Announce Type: new Abstract: Prompt injection poses a critical threat to the safe deployment of large language models, yet existing detection approaches are typically evaluated unde

Stability Implies Redundancy: Delta Attention Selective Halting for Efficient Long-Context Prefilling

arXiv:2604.18103v2 Announce Type: replace Abstract: Prefilling computational costs pose a significant bottleneck for Large Language Models (LLMs) and Large Multimodal Models (LMMs) in long-context set

Hardware

Tensormesh taps Nvidia, AMD and CoreWeave for funding to fix AI model memory problems

Tensormesh Inc. has hit upon a way to make artificial intelligence inference more efficient by eliminating the need for redundant computations, and its technology is so convincing that several of AI i

hardwaresiliconangle

The Bridge-Garden Dilemma in LLM Distillation: Why Mixing Hard and Soft Labels Works

arXiv:2605.26246v1 Announce Type: new Abstract: Knowledge distillation (KD) transfers knowledge from a large teacher model to a smaller student. In language modeling, the student is trained either on

When Does LeJEPA Learn a World Model?

arXiv:2605.26379v1 Announce Type: cross Abstract: A representation that scrambles the true degrees of freedom of the world cannot support reliable planning or compositional generalization. We prove th

safetyarxiv-cs-lg

When LLMs Benchmark Themselves: Deconstructing Self-Bias in Automated Evaluation

arXiv:2509.26600v2 Announce Type: replace-cross Abstract: As LLMs rapidly saturate existing benchmarks, automated benchmark creation using LLMs (LLM-as-a-benchmark) -- where a model generates test inp

Act or Clarify? Modeling Sensitivity to Uncertainty and Cost in Communication

arXiv:2602.02843v3 Announce Type: replace Abstract: When deciding how to act under uncertainty, agents may choose to act to reduce uncertainty or they may act despite that uncertainty. In communicativ

agentsarxiv-cs-cl

An Efficient Learning Method to Connect Observables

arXiv:2503.01684v3 Announce Type: replace-cross Abstract: Constructing fast and accurate surrogate models is a key ingredient for making robust predictions in many topics. We introduce a new model, th

Beyond Inference-Only Deployment: Comparing Weight-Based Consolidation Against Cascading Compaction

arXiv:2605.24657v1 Announce Type: new Abstract: Major LLM platforms deploy models in an inference-only configuration: the model serves requests but never updates per-user weights. Users must repeatedl

Applications

Beyond Static Uncertainty: Modeling Temporal Uncertainty Dynamics for Probabilistic Time Series Forecasting

arXiv:2603.24254v2 Announce Type: replace-cross Abstract: Real-world time series exhibit temporally structured uncertainty: volatility clusters in turbulent regimes, dissipates in stable periods, and

applicationsarxiv-cs-ai

Beyond the Target: From Imitation to Collaboration in Speculative Decoding

arXiv:2605.24793v1 Announce Type: new Abstract: Speculative decoding (SPD) accelerates large language model (LLM) inference by letting a smaller draft model propose multiple future tokens that are ver

safetyarxiv-cs-cl

Research

DRIVE: Modeling Skills at the Reasoning and Interaction Levels for Web Agents under Continual Learning

arXiv:2605.23939v1 Announce Type: new Abstract: Web agents require both high-level reasoning (for task decomposition) and low-level interactions (for page elements manipulation) to conduct different t

researcharxiv-cs-ai

Empirical Analysis and Detection of Hallucinations in LLM-Generated Bug Report Summaries

arXiv:2605.24137v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to generate summaries of software bug reports, including sections such as Steps-to-Reproduce (S2R),

Free the 100B Gemma 4 MoE! Gemini Flash 3.5 is out so now you can release it!

model-releasesclem-delangue--x

Clem Delangue advocates for the release of a 100 billion parameter Gemma 4 Mixture of Experts model, suggesting that Gemini Flash 3.5's release creates an opportunity for this larger model to be made

Improving the Completeness and Comparability of Segment Disclosures: A Large Language Model Approach

arXiv:2605.23924v1 Announce Type: new Abstract: Segment-level disclosures are a central component of financial reporting, providing insight into firms' internal organization and the allocation of econ

safetyarxiv-cs-cl

Applications

Missing Pattern Recognized Diffusion Imputation Model for Missing Not At Random

arXiv:2605.25439v1 Announce Type: new Abstract: Missing data frequently arises across diverse domains, including time-series and image domains. In the real world, missing occurrences often depend on t

applicationsarxiv-cs-lg

Tutorials

Mode-as-Sequence: Translating Multimodal Motion Prediction into Unified Sequential Mode Modeling

arXiv:2605.24037v1 Announce Type: cross Abstract: Multimodal motion forecasting is inherently under-supervised: each training scene provides only one realized future, yet multiple plausible futures ex

tutorialsarxiv-cs-ai

Optimal Design for Multinomial Logit Model with Applications to Best Assortment Identification

arXiv:2605.25592v1 Announce Type: cross Abstract: We study optimal experimental design for multinomial logit (MNL) bandits, where an agent repeatedly selects a subset of K items from a ground set of s

agentsarxiv-cs-lg

Palette: A Modular, Controllable, and Efficient Framework for On-demand Authorized Safety Alignment Relaxation in LLMs

arXiv:2605.24154v1 Announce Type: new Abstract: Current safety alignment of foundation models largely follows a one-size-fits-all paradigm, applying the same refusal policy across users and contexts.

PCGRLLM: Large Language Model-Driven Reward Design for Procedural Content Generation Reinforcement Learning

arXiv:2502.10906v2 Announce Type: replace Abstract: Reward design plays a pivotal role in the training of game AIs, requiring substantial domain-specific knowledge and human effort. In recent years, s

agentsarxiv-cs-ai

SLAP: Stratified Loss-based Pruning for On-Policy Data-Efficient Instruction Tuning

arXiv:2605.23969v1 Announce Type: new Abstract: Instruction tuning has optimized the specialized capabilities of large language models (LLMs), but it often requires extensive datasets and prolonged tr

Research

Subspace Aggregation Query and Index Generation for Multidimensional Resource Space Model

arXiv:2505.02129v3 Announce Type: replace-cross Abstract: Organizing large-scale resources in a multidimensional semantic space is an approach to efficiently managing and querying resources from diffe

researcharxiv-cs-ai