Search: “models”

Towards Context-Invariant Safety Alignment for Large Language Models

arXiv:2605.20994v1 Announce Type: new Abstract: Preference-based post-training aligns LLMs with human intent, yet safety behavior often remains brittle. A model may refuse a harmful request in a stand

safetyarxiv-cs-cl

21 May 2026

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while everyone seems to be focused on text, vision, and audio, i'm excited to be backing a company building a foundational model for smell …

DGX agent

while everyone seems to be focused on text, vision, and audio, i'm excited to be backing a company building a foundational model for smell 👃 that's right, they've: - mapped how olfactory receptors rea

agentsyohei-nakajima--x

21 May 2026

You Don't Need Attention: Gated Convolutional Modeling for Watch-Based Fall Detection

arXiv:2605.20275v1 Announce Type: new Abstract: Existing deep learning approaches for wearable fall detection systems rely on self-attention mechanisms that impose quadratic computational overhead, di

21 May 2026

3D Modeling and Automated Measurement of Concrete Cracks via Segment Anything Refinement and Visual Inertial LiDAR Fusion

arXiv:2501.09203v2 Announce Type: replace Abstract: Visual-Spatial Systems has become increasingly essential in concrete crack inspection. However, existing methods often lacks adaptability to diverse

Industry

a general-purpose model solved a major open problem in mathematics. we'll be saying this a lot over the coming years, but this is a kinda bi…

a general-purpose model solved a major open problem in mathematics. we'll be saying this a lot over the coming years, but this is a kinda big milestone. i'm very excited for AI to greatly extend our u

industrysam-altman--x

Artificial Phantasia: Emergent Mental Imagery in Large Language Models

arXiv:2509.23108v2 Announce Type: replace Abstract: Can visual imagery be driven solely by language? This idea goes against cognitive science's traditional view that visual mental imagery is only poss

BabyMamba-HAR: Lightweight Selective State Space Models for Efficient Human Activity Recognition on Resource Constrained Devices

arXiv:2602.09872v2 Announce Type: replace Abstract: Human activity recognition (HAR) on resource constrained devices requires high accuracy across diverse sensor setups. Selective state space models (

Boosting Text-to-Image Diffusion Models via Core Token Attention-Based Seed Selection

arXiv:2605.19532v1 Announce Type: new Abstract: Text-to-image diffusion models can synthesize high-quality images, yet the outcome is notoriously sensitive to the random seed: different initial seeds

safetyarxiv-cs-cv

Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models

arXiv:2605.19929v1 Announce Type: cross Abstract: Low-bit post-training quantization (PTQ) is a pivotal technique for deploying Vision-Language Models (VLMs) on resource-constrained devices. However,

Contextualized Visual Personalization in Vision-Language Models

arXiv:2602.03454v3 Announce Type: replace Abstract: Despite recent progress in vision-language models (VLMs), existing approaches often fail to generate personalized responses based on the user's spec

researcharxiv-cs-cv

‼️ Could large language models turn out to be the tech industry’s Vietnam? All In’s @jason notes below that today’s students are speaking ou…

‼️ Could large language models turn out to be the tech industry’s Vietnam? All In’s @jason notes below that today’s students are speaking out against AI, just as students in the 60s and 70s spoke out

safetygary-marcus--x

Drifting Objectives for Refining Discrete Diffusion Language Models

arXiv:2605.19470v1 Announce Type: new Abstract: Discrete diffusion language models (DDLMs) generate text by iteratively denoising categorical token sequences, while recent drifting methods for continu

tutorialsarxiv-cs-cl

Faster-GCG: Efficient Discrete Optimization Jailbreak Attacks against Aligned Large Language Models

arXiv:2410.15362v2 Announce Type: replace-cross Abstract: Aligned Large Language Models (LLMs) have attracted significant attention for their safety, particularly in the context of jailbreak attacks t

FieldFormer: Locality-Aware Transformers for Spatio-Temporal Modeling on Sparse Sensor Networks

arXiv:2510.03589v2 Announce Type: replace Abstract: Spatio-temporal sensor data in real-world systems is often sparse, noisy, and irregular, making latent field reconstruction fundamentally underconst

local-aiarxiv-cs-lg

FlyMirage: A Fully Automated Generation Pipeline for Diverse and Scalable UAV Flight Data via Generative World Model

arXiv:2605.19600v1 Announce Type: new Abstract: In the field of Vision-Language Navigation (VLN), aerial datasets remain limited in their ability to combine scale, diversity, and realism, often relyin

applicationsarxiv-cs-ro

GenAI-FDIA: Physics-Informed Generative Models for False Data Injection Attacks

arXiv:2605.18873v1 Announce Type: cross Abstract: Training and evaluating false data injection attack (FDIA) detectors for power systems is constrained by data scarcity. Operational grid measurements

Love this concept. Always been a proponent of event-driven architectures, and the actor model. Neat to see how it’s applied to the agent run…

Love this concept. Always been a proponent of event-driven architectures, and the actor model. Neat to see how it’s applied to the agent runtime here. i'm excited to open source Active Graph: an event

agentsyohei-nakajima--x

Measuring Stereotype and Deviation Biases in Large Language Models

arXiv:2508.06649v3 Announce Type: replace Abstract: Large language models (LLMs) are widely applied across diverse domains, raising concerns about their limitations and potential risks. In this study,

safetyarxiv-cs-cl

Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence

arXiv:2605.18893v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) are powerful tools for learning from graph-structured data, but their scalability is increasingly strained by the size of r

applicationsarxiv-cs-lg

Robotics-Inspired Guardrails for Foundation Models in Socially Sensitive Domains

arXiv:2605.19940v1 Announce Type: new Abstract: Foundation models are increasingly deployed in socially sensitive domains such as education, mental health, and caregiving, where failures are often cum

Rotation-Aligned Key Channel Pruning for Efficient Vision-Language Model Inference

arXiv:2605.19218v1 Announce Type: cross Abstract: Vision-Language Models suffer severe KV cache pressure at inference, as a single image often encodes into thousands of tokens. Most existing methods e

Towards Fine-Grained Robustness: Attention-Guided Test-Time Prompt Tuning for Vision-Language Models

arXiv:2605.19956v1 Announce Type: new Abstract: Vision-Language Models (VLMs), such as CLIP, have achieved significant zero-shot performance on downstream tasks with various fine-tuning adaptation met

tutorialsarxiv-cs-cv

Industry

Vietnam introduces Decree 142 to implement its AI law, requiring companies to classify AI models by risk level, label deepfakes, and disclose chatbot use (Lien Hoang/Nikkei Asia)

Lien Hoang / Nikkei Asia: Vietnam introduces Decree 142 to implement its AI law, requiring companies to classify AI models by risk level, label deepfakes, and disclose chatbot use — HO CHI MINH CITY —

industrytechmeme

We added 600+ new voices on Together AI! Introducing MiniMax Speech 2.8 Turbo on Together AI, an enterprise TTS model for expressive real-ti…

applicationstogether-ai--x

We added 600+ new voices on Together AI! Introducing MiniMax Speech 2.8 Turbo on Together AI, an enterprise TTS model for expressive real-time voice agents. AI natives can now deploy @MiniMax_AI Speec

We are also launching Science Skills, a specialized bundle that integrates insights from 30+ major life science models and databases with ag…

We are also launching Science Skills, a specialized bundle that integrates insights from 30+ major life science models and databases with agentic platforms like @Antigravity to allow researchers to pe

agentsgoogle-ai--x

working on some hex dashboards -- this is a bummer! if you use langchain/deepagents as your agent harness, you can swap models with fallback…

working on some hex dashboards -- this is a bummer! if you use langchain/deepagents as your agent harness, you can swap models with fallback middleware when your first choice provider is down https://

agentsharrison-chase--x

Axial-Relation Guided Fusion State Space Model for Optical-Elevation Sensing Image Segmentation

arXiv:2605.16768v1 Announce Type: new Abstract: Semantic segmentation of multi-source remote sensing images is a fundamental task for Earth observation applications. Existing methods often struggle wi

CanViT: Toward Active-Vision Foundation Models

arXiv:2603.22570v2 Announce Type: replace Abstract: Active computer vision promises efficient, biologically plausible perception through sequential, localized glimpses, but lacks scalable general-purp

CoLLM-NAS: Collaborative Large Language Models for Efficient Knowledge-Guided Neural Architecture Search

arXiv:2509.26037v2 Announce Type: replace Abstract: The integration of Large Language Models (LLMs) with Neural Architecture Search (NAS) has introduced new possibilities for automating the design of

tutorialsarxiv-cs-ai

Confidence Geometry Reveals Trace-Level Correctness in Large Language Model Reasoning

arXiv:2605.16824v1 Announce Type: cross Abstract: Large language models (LLMs) generate not only reasoning text, but also token-level confidence trajectories that record how uncertainty evolves during

Counterparty Modeling is Not Strategy: The Limits of LLM Negotiators

arXiv:2605.16575v1 Announce Type: new Abstract: Negotiation requires more than inferring what the other side wants: it requires using that information to make advantageous offers and counteroffers ove

Industry

customers are increasingly asking us for certainty on capacity. as models get better, we expect that the world will be capacity-constrained …

customers are increasingly asking us for certainty on capacity. as models get better, we expect that the world will be capacity-constrained for some time. we are offering discounted tokens for 1-3 yea

industrysam-altman--x

Does Your Reasoning Model Implicitly Know When to Stop Thinking?

arXiv:2602.08354v5 Announce Type: replace Abstract: Recent advancements in large reasoning models (LRMs) have greatly improved their capabilities on complex reasoning tasks through Long Chains of Thou

DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving

arXiv:2505.16278v2 Announce Type: replace-cross Abstract: End-to-end autonomous driving (E2E-AD) demands effective processing of multi-view sensory data and robust handling of diverse and complex driv

agentsarxiv-cs-ai

Embracing Anisotropy: Turning Massive Activations into Interpretable Control Knobs for Large Language Models

arXiv:2603.00029v2 Announce Type: replace Abstract: Large Language Models (LLMs) exhibit highly anisotropic internal representations, often characterized by massive activations, a phenomenon where a s

Finding Sense in Nonsense with Generated Contexts: Perspectives from Humans and Language Models

arXiv:2602.11699v3 Announce Type: replace Abstract: Nonsensical and anomalous sentences have been instrumental in the development of computational models of semantic interpretation. A core challenge i

Flow-Direct: Feedback-Efficient and Reusable Guidance for Flow Models via Non-Parametric Guidance Field

arXiv:2605.16348v1 Announce Type: cross Abstract: Training-free guidance enables pre-trained diffusion and flow models to optimize application-specific objectives using feedback from external black-bo

Forgetting is Competition: Rethinking Unlearning as Representation Interference in Diffusion Models

arXiv:2603.00975v2 Announce Type: replace-cross Abstract: Deployed text-to-image diffusion models increasingly require post-hoc concept unlearning for copyright claims, artist opt-outs, safety updates

From Demographics to Survey Anchors: Evaluating LLM Agents for Modeling Retirement Attitudes

arXiv:2605.16303v1 Announce Type: cross Abstract: Large language models (LLM) agents may offer tools to predict human responses to surveys. A common technique for defining these agents uses only demog

It is really good at instruction following, obviously, and having a smart model capable of doing video expands what you can do by a consider…

applicationsethan-mollick--x

Ethan Mollick discusses how a model's instruction-following capabilities and video processing abilities expand its potential applications and use cases. He emphasizes that combining strong instruction

Language Acquisition Device in Large Language Models

arXiv:2605.16758v1 Announce Type: new Abstract: Large Language Models (LLMs) remain substantially less data-efficient than humans. Pre-pretraining (PPT) on synthetic languages has been proposed to clo

Learning What Evaluators Value: A Reliable Approach to Modeling Evaluator Preferences

arXiv:2605.16615v1 Announce Type: new Abstract: In many applications, human and LLM evaluators use assessments of relevant criteria to create an overall evaluation for an item or individual. For examp

tutorialsarxiv-cs-lg

Leveraging Graph Structure in Seq2Seq Models for Knowledge Graph Link Prediction

arXiv:2605.18211v1 Announce Type: cross Abstract: We introduce Graph-Augmented Sequence-to-Sequence (GA-S2S), a novel framework that integrates a T5-small encoder-decoder with a Relational Graph Atten

Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Model

arXiv:2512.01030v3 Announce Type: replace Abstract: Recovering pixel-wise geometric properties from a single image is fundamentally ill-posed due to appearance ambiguity and non-injective mappings bet

researcharxiv-cs-cv

Mitigating 3D Prostate Biparametric MRI Data Scarcity through Domain Adaptation using Locally-Trained Latent Diffusion Models for Prostate Cancer Detection

arXiv:2507.06384v2 Announce Type: replace-cross Abstract: Objective: Latent diffusion models (LDMs) could mitigate data scarcity challenges affecting machine learning development for medical image int

researcharxiv-cs-cv

MoleCode unlocks structural intelligence in large language models

arXiv:2605.16480v1 Announce Type: cross Abstract: Molecules are graphs, but large language models~(LLMs) are usually asked to reason about them through linear strings. The most popular molecular repre

Need advice: Best ComfyUl workflow for texturing a 3D model from 4 orthographic views using reference images?

local-air-stablediffusion

A Reddit user seeks guidance on configuring ComfyUI workflows to texture 3D models using orthographic reference images from multiple angles. The discussion likely covers best practices for using Stabl

On the Adversarial Robustness of Large Vision-Language Models under Visual Token Compression

arXiv:2601.21531v2 Announce Type: replace-cross Abstract: Visual token compression is widely used to accelerate large vision-language models (LVLMs) by pruning or merging visual tokens, yet its advers