Search: “models”

RISE: Self-Improving Robot Policy with Compositional World Model

arXiv:2602.11075v2 Announce Type: replace Abstract: Despite the sustained scaling on model capacity and data acquisition, Vision-Language-Action (VLA) models remain brittle in contact-rich and dynamic

safetyarxiv-cs-ro

29 Apr 2026

Why Does Reinforcement Learning Generalize? A Feature-Level Mechanistic Study of Post-Training in Large Language Models

DGX agent

arXiv:2604.25011v1 Announce Type: new Abstract: Reinforcement learning (RL)-based post-training often improves the reasoning performance of large language models (LLMs) beyond the training domain, whi

researcharxiv-cs-cl

29 Apr 2026

A systematic evaluation of vision-language models for observational astronomical reasoning tasks

arXiv:2604.24589v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly proposed as general-purpose tools for scientific data interpretation, yet their reliability on real astro

Au-M-ol: A Unified Model for Medical Audio and Language Understanding

arXiv:2604.23284v1 Announce Type: cross Abstract: In this work, we present Au-M-ol, a novel multimodal architecture that extends Large Language Models (LLMs) with audio processing. It is designed to i

applicationsarxiv-cs-ai

Channel Adaptation for EEG Foundation Models: A Systematic Benchmark Across Architectures, Tasks, and Training Regimes

model-releasesarxiv-cs-lg

arXiv:2604.23091v1 Announce Type: new Abstract: Scaling EEG foundation models requires pooling data across heterogeneous electrode montages, a prerequisite both for larger pretraining corpora and for

Energy-Aware Routing to Large Reasoning Models

arXiv:2601.00823v2 Announce Type: replace Abstract: Large reasoning models (LRMs) have heterogeneous inference energy costs based on which model is used and how much it reasons. To reduce energy, it i

Learning an Image Editing Model without Image Editing Pairs

arXiv:2510.14978v2 Announce Type: replace Abstract: Recent image editing models have achieved impressive results while following natural language editing instructions, but they rely on supervised fine

researcharxiv-cs-cv

Measuring Temporal Linguistic Emergence in Diffusion Language Models

arXiv:2604.23235v1 Announce Type: new Abstract: Diffusion language models expose an explicit denoising trajectory, making it possible to ask when different kinds of information become measurable durin

MetaEarth3D: Unlocking World-scale 3D Generation with Spatially Scalable Generative Modeling

arXiv:2604.22828v1 Announce Type: cross Abstract: Recent generative AI models have achieved remarkable breakthroughs in language and visual understanding. However, although these models can generate r

applicationsarxiv-cs-ai

On Emergent Social World Models -- Evidence for Functional Integration of Theory of Mind and Pragmatic Reasoning in Language Models

arXiv:2602.10298v2 Announce Type: replace Abstract: This paper investigates whether LMs recruit shared computational mechanisms for general Theory of Mind (ToM) and language-specific pragmatic reasoni

On the Reasoning Abilities of Masked Diffusion Language Models

arXiv:2510.13117v3 Announce Type: replace-cross Abstract: Masked diffusion models (MDMs) for text offer a compelling alternative to traditional autoregressive language models. Parallel generation make

The Randomness Floor: Measuring Intrinsic Non-Randomness in Language Model Token Distributions

arXiv:2604.22771v1 Announce Type: cross Abstract: Language models cannot be random. This paper introduces Entropic Deviation (ED), the normalised KL divergence between a model's token distribution and

Local Ai

Differentiable Filtering for Learning Hidden Markov Models

arXiv:2511.10571v2 Announce Type: replace Abstract: Hidden Markov Models (HMMs) are fundamental for modeling sequential data, yet learning their parameters from observations remains challenging. Class

local-aiarxiv-cs-lg

27 Apr 2026

Language Specific Knowledge: Do Models Know Better in X than in English?

arXiv:2505.14990v3 Announce Type: replace Abstract: Often, multilingual language models are trained with the objective to map semantically similar content (in different languages) in the same latent s

27 Apr 2026

When LoRA Betrays: Backdooring Text-to-Image Models by Masquerading as Benign Adapters

arXiv:2602.21977v4 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has emerged as a leading technique for efficiently fine-tuning text-to-image diffusion models, and its widespread adoptio

researcharxiv-cs-cv

27 Apr 2026

ChessArena: A Chess Testbed for Evaluating Strategic Reasoning Capabilities of Large Language Models

arXiv:2509.24239v4 Announce Type: replace-cross Abstract: Recent large language models (LLMs) have shown strong reasoning capabilities. However, a critical question remains: do these models possess ge

Hi-WM: Human-in-the-World-Model for Scalable Robot Post-Training

arXiv:2604.21741v1 Announce Type: new Abstract: Post-training is essential for turning pretrained generalist robot policies into reliable task-specific controllers, but existing human-in-the-loop pipe

safetyarxiv-cs-ro

More of my notes on DeepSeek V4 - the really big news is the pricing: both DeepSeek-V4-Flash and DeepSeek-V4-Pro are the cheapest models in …

model-releasessimon-willison--x

More of my notes on DeepSeek V4 - the really big news is the pricing: both DeepSeek-V4-Flash and DeepSeek-V4-Pro are the cheapest models in their categories while benchmarking close to the frontier mo

Pretrain Where? Investigating How Pretraining Data Diversity Impacts Geospatial Foundation Model Performance

model-releasesarxiv-cs-cv

arXiv:2604.21104v1 Announce Type: new Abstract: New geospatial foundation models introduce a new model architecture and pretraining dataset, often sampled using different notions of data diversity. Pe

Revealing Geography-Driven Signals in Zone-Level Claim Frequency Models: An Empirical Study using Environmental and Visual Predictors

model-releasesarxiv-cs-lg

arXiv:2604.21893v1 Announce Type: cross Abstract: Geographic context is often consider relevant to motor insurance risk, yet public actuarial datasets provide limited location identifiers, constrainin

VLA-Forget: Vision-Language-Action Unlearning for Embodied Foundation Models

arXiv:2604.03956v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models are emerging as embodied foundation models for robotic manipulation, but their deployment introduces a new

safetyarxiv-cs-ai

LayerTracer: A Joint Task-Particle and Vulnerable-Layer Analysis framework for Arbitrary Large Language Model Architectures

arXiv:2604.20556v1 Announce Type: cross Abstract: Currently, Large Language Models (LLMs) feature a diversified architectural landscape, including traditional Transformer, GateDeltaNet, and Mamba. How

23 Apr 2026

AlignCultura: Towards Culturally Aligned Large Language Models?

arXiv:2604.19016v1 Announce Type: new Abstract: Cultural alignment in Large Language Models (LLMs) is essential for producing contextually aware, respectful, and trustworthy outputs. Without it, model

Local Ai

Automated Energy-Aware Time-Series Model Deployment on Embedded FPGAs for Resilient Combined Sewer Overflow Management

arXiv:2508.13905v2 Announce Type: replace Abstract: Extreme weather events, intensified by climate change, increasingly challenge aging combined sewer systems, raising the risk of untreated wastewater

local-aiarxiv-cs-lg

Dynamic Model Routing and Cascading for Efficient LLM Inference: A Survey

arXiv:2603.04445v2 Announce Type: replace-cross Abstract: The rapid growth of large language models (LLMs) with diverse capabilities, costs, and domains has created a critical need for intelligent mod

Fine-Tuning Small Reasoning Models for Quantum Field Theory

arXiv:2604.18936v1 Announce Type: cross Abstract: Despite the growing application of Large Language Models (LLMs) to theoretical physics, there is little academic exploration into how domain-specific

How Far Are Video Models from True Multimodal Reasoning?

model-releasesarxiv-cs-cv

arXiv:2604.19193v1 Announce Type: new Abstract: Despite remarkable progress toward general-purpose video models, a critical question remains unanswered: how far are these models from achieving true mu

LLM-as-Judge Framework for Evaluating Tone-Induced Hallucination in Vision-Language Models

arXiv:2604.18803v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly deployed in settings where reliable visual grounding carries operational consequences, yet their behavi

Multilingual Language Models Encode Script Over Linguistic Structure

arXiv:2604.05090v2 Announce Type: replace Abstract: Multilingual language models (LMs) organize representations for typologically and orthographically diverse languages into a shared parameter space,

QSLM: A Performance- and Memory-aware Quantization Framework with Tiered Search Strategy for Spike-driven Language Models

arXiv:2601.00679v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have been emerging as prominent AI models for solving many natural language tasks due to their high performance (

Characterizing Model-Native Skills

arXiv:2604.17614v1 Announce Type: cross Abstract: Skills are a natural unit for describing what a language model can do and how its behavior can be changed. However, existing characterizations rely on

safetyarxiv-cs-cl

Cross-Family Speculative Decoding for Polish Language Models on Apple~Silicon: An Empirical Evaluation of Bielik~11B with UAG-Extended MLX-LM

arXiv:2604.16368v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by using a small draft model to propose k candidate tokens for a target model to verify. While effective

Injecting Structured Biomedical Knowledge into Language Models: Continual Pretraining vs. GraphRAG

arXiv:2604.16422v1 Announce Type: new Abstract: The injection of domain-specific knowledge is crucial for adapting language models (LMs) to specialized fields such as biomedicine. While most current a

JudgeMeNot: Personalizing Large Language Models to Emulate Judicial Reasoning in Hebrew

arXiv:2604.18041v1 Announce Type: new Abstract: Despite significant advances in large language models, personalizing them for individual decision-makers remains an open problem. Here, we introduce a s

LogicDiff: Logic-Guided Denoising Improves Zero-Shot Reasoning in Masked Diffusion Language Models

arXiv:2603.26771v2 Announce Type: replace Abstract: Masked diffusion language models (MDLMs) generate text by iteratively unmasking tokens from a fully masked sequence. Their standard confidence-based

Reasoning Models Know What's Important, and Encode It in Their Activations

arXiv:2604.18307v1 Announce Type: new Abstract: Language models often solve complex tasks by generating long reasoning chains, consisting of many steps with varying importance. While some steps are cr

Scaling Recurrence-aware Foundation Models for Clinical Records via Next-Visit Prediction

model-releasesarxiv-cs-lg

arXiv:2603.24562v2 Announce Type: replace Abstract: While large-scale pretraining has revolutionized language modeling, its potential remains underexplored in healthcare with structured electronic hea

Sharpening Lightweight Models for Generalized Polyp Segmentation: A Boundary Guided Distillation from Foundation Models

arXiv:2604.17865v1 Announce Type: new Abstract: Automated polyp segmentation is critical for early colorectal cancer detection and its prevention, yet remains challenging due to weak boundaries, large

safetyarxiv-cs-cv

SIF: Semantically In-Distribution Fingerprints for Large Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2604.17041v1 Announce Type: new Abstract: The public accessibility of large vision-language models (LVLMs) raises serious concerns about unauthorized model reuse and intellectual property infrin

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks

arXiv:2604.17159v1 Announce Type: cross Abstract: We present, to our knowledge, the most comprehensive cross-model evaluation of LLM agents on offensive cybersecurity tasks, benchmarking 10 frontier m

The Illusion of Insight in Reasoning Models

arXiv:2601.00514v2 Announce Type: replace-cross Abstract: Do reasoning models have 'Aha!' moments? Prior work suggests that models like DeepSeek-R1-Zero undergo sudden mid-trace realizations that lead

Tutorials

Towards a Foundation-Model Paradigm for Aerodynamic Prediction in Three-dimensional Design

arXiv:2604.18062v1 Announce Type: new Abstract: Accurate machine-learning models for aerodynamic prediction are essential for accelerating shape optimization, yet remain challenging to develop for com

tutorialsarxiv-cs-lg

VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction

arXiv:2505.20279v4 Announce Type: replace-cross Abstract: The rapid advancement of Large Multimodal Models (LMMs) for 2D images and videos has motivated extending these models to understand 3D scenes,

Boston Dynamics just gave its robot dog a brain that reasons about the physical world. Google DeepMind's Gemini Robotics model is now runnin…

model-releasesrowan-cheung--x

Boston Dynamics just gave its robot dog a brain that reasons about the physical world. Google DeepMind's Gemini Robotics model is now running inside Spot, the four-legged robot already deployed at tho

Evaluating the Progression of Large Language Model Capabilities for Small-Molecule Drug Design

arXiv:2604.16279v1 Announce Type: new Abstract: Large Language Models (LLMs) have the potential to accelerate small molecule drug design due to their ability to reason about information from diverse s

applicationsarxiv-cs-lg

Fragile Thoughts: How Large Language Models Handle Chain-of-Thought Perturbations

arXiv:2603.03332v3 Announce Type: replace-cross Abstract: Chain-of-Thought (CoT) prompting has emerged as a foundational technique for eliciting reasoning from Large Language Models (LLMs), yet the ro

Information Router for Mitigating Modality Dominance in Vision-Language Models

arXiv:2604.16264v1 Announce Type: new Abstract: Vision Language models (VLMs) have demonstrated strong performance across a wide range of benchmarks, yet they often suffer from modality dominance, whe

applicationsarxiv-cs-cv

Language Models as Semantic Teachers: Post-Training Alignment for Medical Audio Understanding

arXiv:2512.04847v2 Announce Type: replace-cross Abstract: Pre-trained audio models excel at detecting acoustic patterns in auscultation sounds but often fail to grasp their clinical significance, limi

safetyarxiv-cs-ai