Search: “models”

What's in a Name? Morphological Shortcuts by LLMs in Pharmacology

arXiv:2606.05616v1 Announce Type: new Abstract: The morphological form of a word can often give cues to its meaning, but purely relying on these mappings can lead to overgeneralization in high-stakes

safetyarxiv-cs-cl

5 Jun 2026

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer

DGX agent

arXiv:2606.05626v1 Announce Type: new Abstract: Machine-generated text (MGT) attribution aims to identify the specific generator responsible for a given text, thereby providing fine-grained evidence f

researcharxiv-cs-cl

5 Jun 2026

ACAT: A Collaborative Platform for Efficient Aspect-Based Sentiment Dataset Annotation

arXiv:2606.04189v1 Announce Type: new Abstract: Aspect-Based Sentiment Analysis (ABSA) requires high-quality datasets to train reliable models. However, existing annotation tools treat output as flat

Industry

AI startup Flourish reportedly raises $500M round backed by Jeff Bezos

Flourish Inc., a startup developing artificial intelligence models inspired by the human brain, has raised 500 million in funding at a 2.5 billion valuation. Wired reported today that about a fifth of

industrysiliconangle

Tools

[AINews] Reve 2 and Ideogram 4: Layouts in Imagegen

This AI News summary covers recent developments in image generation models, specifically discussing Reve 2 and Ideogram 4's layout capabilities for creating structured visual designs. The piece likely

toolslatent-space

Applications

As enterprise AI matures, data and context emerge as new competitive edge

Enterprise AI is entering a new phase where competitive advantage depends less on foundation models and more on the ability to connect data and business knowledge through an enterprise context layer.

applicationssiliconangle

Applications

BEATS: Bootstrapping E-commerce Attribute Taxonomies for Search through Iterative Human-AI Collaboration

arXiv:2606.04909v1 Announce Type: cross Abstract: E-commerce platforms in emerging markets often operate with underdeveloped product catalogs that contain only category taxonomies but lack structured

applicationsarxiv-cs-cl

Industry

Cable lobby warns of chaos if FCC doesn't relax ban on foreign routers

In March 2026, the FCC added all consumer-grade routers produced in foreign countries to its Covered List, prohibiting new models from receiving authorization . The ban cites supply chain vulnerabilit

industryars-technica

Call your Hermes Agent

This post likely announces or describes how to invoke or utilize a Hermes Agent, possibly related to function calling, tool use, or agentic capabilities within the Hermes model framework developed by

agentsnous-research--x

Hardware

Cartridges at Scale: Training Modular KV Caches over Large Document Collections

arXiv:2606.04557v1 Announce Type: new Abstract: Large Language Models can reason over long contexts, yet prefilling millions of tokens is wasteful as much of the content remains static across queries.

hardwarearxiv-cs-cl

CleanCodec: Efficient and Robust Speech Tokenization via Perceptually Guided Encoding

arXiv:2606.04418v1 Announce Type: cross Abstract: Neural audio codecs are a key component of speech processing pipelines, compressing audio into discrete tokens for downstream modeling. However, exist

Constrained Adaptive Rejection Sampling

arXiv:2510.01902v2 Announce Type: replace Abstract: Language Models (LMs) are increasingly used in applications where generated outputs must satisfy strict semantic or syntactic constraints. Existing

Continuum Robot State Estimation with Actuation Uncertainty

arXiv:2601.04493v3 Announce Type: replace Abstract: Continuum robots are flexible, slender manipulators well suited for confined surgical environments. In these settings, unknown interaction forces an

researcharxiv-cs-ro

CRAFT: Cost-aware Refinement And Front-aware Tuning of Prompts

arXiv:2606.04661v1 Announce Type: new Abstract: Prompts tuned for accuracy often grow long, raising inference cost on every model call. The best accuracy-cost trade-off depends on the task and the bud

DAR: Deontic Reasoning with Agentic Harnesses

arXiv:2606.05009v1 Announce Type: cross Abstract: Deontic reasoning is the task of answering questions by applying explicit rules and policies to case-specific facts, for example computing tax liabili

agentsarxiv-cs-ai

Decentralized EM Algorithm for Gaussian Mixtures under Data Heterogeneity and Partial Labeling

arXiv:2411.05591v2 Announce Type: replace-cross Abstract: We systematically study several network-based Expectation-Maximization (EM) algorithms for the Gaussian mixture model within decentralized fed

Drift-Augmented Scoring: Text-Derived Noise Robustness for Zero-Shot Audio-Language Classification

arXiv:2606.04844v1 Announce Type: cross Abstract: Contrastive audio-language models such as CLAP enable zero-shot audio classification: a sound is labelled by matching its embedding to text prompt emb

researcharxiv-cs-cv

Hardware

DSA: Dynamic Step Allocation for Fast Autoregressive Video Generation

arXiv:2606.04432v1 Announce Type: new Abstract: Video diffusion transformers have achieved state-of-the-art visual quality, but their high inference cost remains a major bottleneck for real-time appli

hardwarearxiv-cs-cv

EpiFormer: Learning Antigen-Antibody Interactions for Epitope Prediction via Geometric Deep Learning

arXiv:2606.04154v1 Announce Type: cross Abstract: Antibodies neutralize foreign antigens by binding to specific surface regions called epitopes. Computational epitope prediction is critical for unders

EvalStop: Using World Feedback to Detect and Correct Reward Overoptimization in Multi-Tenant RLHF Platforms

arXiv:2606.04145v1 Announce Type: cross Abstract: Cloud LLM fine-tuning platforms increasingly serve RLHF workloads, where a learned reward model is optimized as a proxy for human quality. As Gao et a

Explaining a probabilistic prediction on the simplex with Shapley compositions

arXiv:2408.01382v3 Announce Type: replace Abstract: Originating in game theory, Shapley values are widely used for explaining a machine learning model's prediction by quantifying the contribution of e

Failed Reasoning Traces Tell You What Is Fixable (But Not by Reading Them)

arXiv:2606.05145v1 Announce Type: cross Abstract: When post-trained language models fail on reasoning problems, the common test-time-scaling response is to spend more compute on additional attempts, a

Fast & Faithful Function Vectors

arXiv:2606.05079v1 Announce Type: new Abstract: Function vectors (FVs) are task representations elicited during in-context learning that can be used to steer Large Language Models (LLMs). However, des

Finite-Iteration Local Dynamics and Warm Starts for Alternating Power Iteration in Spiked Tensor PCA

arXiv:2606.04065v1 Announce Type: cross Abstract: We study simultaneous alternating power iteration for fixed-order asymmetric rank-one spiked tensor models. Our main contribution is a finite-iteratio

Industry

Grok on Cloudflare

Grok on Cloudflare We're partnering with @xai to bring Grok to @Cloudflare AI Gateway. • Grok LLMs, audio, image, and video models are now available through AI Gateway • Billed directly through Cloudf

industryelon-musk--x

Identifying Gems from Roman RAPIDly

arXiv:2606.05103v1 Announce Type: cross Abstract: The Nancy Grace Roman Space Telescope (Roman), set for launch as early as September 2026, will conduct wide-field infrared imaging surveys with unprec

local-aiarxiv-cs-cv

if you had 100k to invest in OpenAI and/or Anthropic IPOs which would you go for?

Gary Marcus discusses investment strategy between potential OpenAI and Anthropic IPOs, likely weighing factors such as the companies' technological capabilities, market positioning, business models, a

safetygary-marcus--x

In-Context Graphical Inference

arXiv:2606.05042v1 Announce Type: cross Abstract: Marginal inference in discrete graphical models forces a choice between exactness and scalability: exact algorithms are intractable for high-treewidth

safetyarxiv-cs-cl

Intra-Modal Neighbors Never Lie: Rectifying Inter-Modal Noisy Correspondence via Graph-Based Intra-Modal Reasoning

arXiv:2606.04061v1 Announce Type: new Abstract: Large-scale web-harvested datasets have fueled the progress of cross-modal retrieval but inevitably suffer from noisy correspondence, which severely deg

researcharxiv-cs-cv

LazyAttention: Efficient Retrieval-Augmented Generation with Deferred Positional Encoding

arXiv:2606.04302v1 Announce Type: new Abstract: Key-value (KV) caching accelerates inference of large language models (LLMs) by reusing past computations for generated tokens. Its importance becomes e

Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers

arXiv:2601.07036v2 Announce Type: replace-cross Abstract: Hybrid reasoning language models are commonly controlled through high-level Think/No-think instructions to regulate reasoning behavior, yet we

Tutorials

Motion-Guided Causal Disentanglement for Robust Multi-View Cine Cardiac MRI Diagnosis

arXiv:2606.04414v1 Announce Type: new Abstract: Multi-view cardiac magnetic resonance (CMR) imaging provides complementary anatomical information and is widely used for noninvasive disease assessment.

tutorialsarxiv-cs-cv

okay but need to save some $$$ for tokens

This post likely discusses cost optimization strategies for managing API token usage and expenses, particularly relevant to users of language models or LLM-based services. The author emphasizes the pr

agentsjerry-liu--x

Optimizing the Cost-Quality Tradeoff of Agentic Theorem Provers in Lean

arXiv:2606.04883v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in workflows for generating formal proofs in Lean. These workflows often decompose problems into smal

agentsarxiv-cs-cl

Tutorials

ParetoPilot: Zero-Surrogate Offline Multi-Objective Optimization via Infer-Perturb-Guide Diffusion

arXiv:2606.04468v1 Announce Type: cross Abstract: Offline multi-objective optimization (Offline MOO) aims to discover novel Pareto-optimal designs based on static datasets without expensive environmen

tutorialsarxiv-cs-ai

Potential-Guided Flow Matching for Vision-Language-Action Policy Improvement

arXiv:2606.04968v1 Announce Type: new Abstract: Large vision-language-action (VLA) policies are increasingly trained as conditional generative models over action chunks. Yet deployment produces mixed-

safetyarxiv-cs-ro

Rethinking Sales Lead Scoring with LLM-based Hierarchical Preference Ranking

arXiv:2606.04387v1 Announce Type: cross Abstract: Sales lead conversion in high-stakes domains (e.g., automotive, real estate) differs fundamentally from e-commerce recommendation due to prolonged dec

safetyarxiv-cs-ai

RL Excursions during Pre-Training: Re-examining Policy Optimization for LLM training

arXiv:2606.04272v1 Announce Type: new Abstract: The standard LLM training pipeline applies reinforcement learning (RL) only after pre-training and supervised fine-tuning (SFT). We question this status

Self-Distilled Policy Gradient

arXiv:2606.04036v1 Announce Type: new Abstract: On-policy self-distillation, where a language model conditions on privileged context to supervise its own generations, is a promising source of dense su

SemBlock: Semantic Boundary Dynamic Blocks for Diffusion LLMs

arXiv:2606.04964v1 Announce Type: new Abstract: Diffusion language models (DLMs) generate text through iterative denoising, and blockwise decoding improves their practicality by committing tokens in l

local-aiarxiv-cs-cl

Sequential Data Poisoning in LLM Post-Training

arXiv:2606.04929v1 Announce Type: new Abstract: LLM post-training proceeds through multiple stages, e.g., supervised fine-tuning (SFT) followed by reinforcement learning from human feedback (RLHF) or

Testing Neural Networks via Bayesian-Guided Exploration of Decision Landscapes

arXiv:2606.04314v1 Announce Type: new Abstract: As neural networks are increasingly deployed in safety-critical domains, testing is essential to evaluate and improve their reliability. Existing testin

The Right Measure for Physics-Constrained Generation: A Co-Area Correction for Posterior-Consistent PDE Inverse Problems

arXiv:2606.04804v1 Announce Type: new Abstract: Generative models -- diffusion and flow matching -- are increasingly used to solve partial differential equation (PDE) inverse problems, enforcing the g

Uncertainty-Aware (Un)Supervised Few-Shot User Adaptation for On-Device Personalized Human Activity Recognition

arXiv:2606.04798v1 Announce Type: new Abstract: Sensor-based Human Activity Recognition (HAR) models often degrade on unseen users due to domain shifts caused by individual movement patterns and senso

local-aiarxiv-cs-lg

Uncertainty Estimation using Variance-Gated Distributions

arXiv:2509.08846v2 Announce Type: replace-cross Abstract: Evaluation of per-sample uncertainty quantification from neural networks is essential for decision-making involving high-risk applications. A

UniFine: A Unified and Fine-grained Approach for Zero-shot Vision-Language Understanding

arXiv:2307.00862v3 Announce Type: replace-cross Abstract: Vision-language tasks, such as VQA, SNLI-VE, and VCR are challenging because they require the model's reasoning ability to understand the sema

Unifying Information-Theoretic and Pair-Counting Clustering Similarity

arXiv:2511.03000v2 Announce Type: replace-cross Abstract: Comparing clusterings is central to evaluating unsupervised models, yet the many existing similarity measures can produce widely divergent, so

v0.30.5

v0.30.5 is a release candidate version of Ollama, a local large language model runner. The v0.30 series features improved compatibility and performance using llama.cpp and augments the MLX engine on A

local-aiollama-releases