Search: “models”

arXiv:2605.00436v1 Announce Type: new Abstract: Concerns with the safety and reliability of applying large-language models (LLMs) in unpredictable real-world applications motivate this study, which ex

arXiv:2605.00384v1 Announce Type: new Abstract: Preference-based reinforcement learning offers a scalable alternative to manual reward engineering by learning reward structures from comparative feedba

arXiv:2605.00022v1 Announce Type: new Abstract: The rapid proliferation of large audio models (LAMs) demands efficient approaches for model comparison, yet comprehensive benchmarks are costly. To fill

arXiv:2501.00885v2 Announce Type: replace Abstract: The extraordinary success of recent Large Language Models (LLMs) on a diverse array of tasks has led to an explosion of scientific and philosophical

arXiv:2512.12744v3 Announce Type: replace Abstract: Activation sparsity offers a compelling route to accelerate large language model (LLM) inference by selectively suppressing hidden activations, yet

arXiv:2605.00364v1 Announce Type: new Abstract: Machine unlearning has emerged as a critical capability for addressing privacy, safety, and regulatory concerns in large language models (LLMs). Existin

An open-source locally-run conversational AI that moves beyond simple request-response models by implementing persistent memory, belief, and self-reflection. The system stores all user profiles, memor

Sakana AI Labs has developed Fugu, a multi-agent orchestration system designed to function as a foundation model. The system likely enables coordinated interaction between multiple AI agents to improv

Sam Altman reflects on the trade-off between model performance improvements and practical considerations like cost and speed, suggesting that increased intelligence remains a primary focus despite use

For programming tasks with an RTX 5080 (16GB VRAM) and 64GB RAM, optimal quantized models include Qwen 3 14B at Q6 quantization, Llama 3.1 13B at Q8, or DeepSeek R1 Distill 14B Q4, all of which fit co

arXiv:2604.27849v1 Announce Type: new Abstract: This paper presents a configurable, grid-aware Agent-Based Model (ABM) for the systematic analysis of electric vehicle (EV) charging systems under confi

arXiv:2508.12022v2 Announce Type: replace Abstract: Major Depressive Disorder is one of the leading causes of disability worldwide, yet its diagnosis still depends largely on subjective clinical asses

arXiv:2512.22046v2 Announce Type: replace Abstract: Prompt-driven Video Segmentation Foundation Models (VSFMs), such as SAM2, are increasingly used in applications including autonomous driving and dig

arXiv:2604.27405v1 Announce Type: cross Abstract: We adapted the Reliable Change Index (RCI; Jacobson and Truax, 1991) from clinical psychology to item-level LLM version comparison on 2,000 MMLU-Pro i

arXiv:2604.26981v1 Announce Type: cross Abstract: Large Language Models (LLMs) have revolutionized the field of natural language processing. However, they exhibit some limitations, including a lack of

arXiv:2604.27361v1 Announce Type: new Abstract: Synthesizing realistic 3D indoor scenes remains challenging due to data scarcity and the difficulty of simultaneously enforcing global architectural con

arXiv:2604.27137v1 Announce Type: new Abstract: This paper introduces a systematic evaluation framework grounded in the Interagency Language Roundtable (ILR) Skill Level Descriptions and applies it to

arXiv:2604.27411v1 Announce Type: new Abstract: Visual model-based reinforcement learning (MBRL) agents can perform well on the training distribution, but often break down once the test environment sh

arXiv:2603.02226v2 Announce Type: replace Abstract: Real-world sequential signals, such as audio or video, contain critical information that is often embedded within long periods of silence or noise.

arXiv:2604.27454v1 Announce Type: new Abstract: Large language models (LLMs) sometimes exhibit qualitative shifts in response style under sustained self-referential dialogue conditions (Berg et al., 2

arXiv:2604.27186v1 Announce Type: cross Abstract: We study finite-horizon budget allocation as a closed-loop economic control problem and evaluate receding-horizon Model Predictive Control (MPC) relat

arXiv:2604.27279v1 Announce Type: cross Abstract: Audio-based stuttering systems to date have been trained for detection -- what disfluency is present now -- leaving prediction, the capability needed

arXiv:2604.27379v1 Announce Type: new Abstract: Dialogue models are inherently reactive, responding to the current user turn without anticipating upcoming intents, which leads to redundant interaction

arXiv:2604.28075v1 Announce Type: cross Abstract: Recent research has shown that filtering massive English web corpora into high-quality subsets significantly improves training efficiency. However, fo

arXiv:2604.27447v1 Announce Type: cross Abstract: Modern stochastic optimization pipelines increasingly rely on learned generative models to represent uncertainty, while downstream decisions are evalu

arXiv:2604.27169v1 Announce Type: new Abstract: We show that the geometric relations between semantic features in large language models' hidden states closely mirror human psychological associations.

arXiv:2604.27899v1 Announce Type: new Abstract: Understanding how human health changes over time, and why responses to interventions vary between individuals, remains a central challenge in medicine.

arXiv:2604.27673v1 Announce Type: new Abstract: We introduce Target-Event-Agent Networks (TEA Nets) as a computational framework to extract subjects (``Agents'), verbs (``Events'), and objects (``Targ

arXiv:2506.05412v3 Announce Type: replace-cross Abstract: Where someone looks is a nonverbal communication cue that children and adults readily use. How well can Vision-Language Models (VLMs) infer ga

You don't have to choose between either. It's best to use a combination of them. My advice is to learn how to use a few of these models in different harnesses. Learn to combine their strengths. Open-w

arXiv:2604.26351v1 Announce Type: new Abstract: Language models (LMs) behave more like humans when their cognitive resources are restricted, particularly in predicting sentence processing costs such a

arXiv:2405.13729v3 Announce Type: replace-cross Abstract: In this paper, we study an under-explored but important factor of diffusion generative models, i.e., the combinatorial complexity. Data sample

arXiv:2604.26503v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in synthesizing complex static and temporal visuals, a breakthrough largely driven by Classifier-Free

arXiv:2604.26256v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a critical paradigm for LLM post-training, yet the rollout phase -- accounting for 50--80% of total step time --

arXiv:2604.26052v1 Announce Type: new Abstract: Safety evaluations of large language models (LLMs) typically report binary outcomes such as attack success rate, refusal rate, or harmful/not-harmful re

arXiv:2604.26139v1 Announce Type: new Abstract: Diffusion large language models generate text through multi-step denoising, where hallucination signals may emerge throughout the trajectory rather than

i havent done the work to compare it to peers but i'm just excited that we have a base model and honestly for all the people that complained about the death of the completions API (@deepfates ? or dee

Elon Musk allegedly admitted during legal testimony that xAI is distilling OpenAI models to train its own systems and utilizing OpenAI's technology, according to a post by Clem Delangue discussing sta

arXiv:2604.26569v1 Announce Type: new Abstract: Deploying a neuro-symbolic task planner on a new domain today requires significant manual effort: a domain expert must author relaxation and complementa

Our agent harness makes models inside Cursor faster, smarter, and more token-efficient. Here's how we test improvements to the harness, monitor and repair degradations, and customize it for different

Normalizing flows (NFs) are end-to-end likelihood-based generative models for continuous data, and have recently regained attention with encouraging progress on image generation. Yet in the video gene

arXiv:2604.26898v1 Announce Type: cross Abstract: We prove pathwise convergence of the layerwise evolution of tokens in a finite-depth, finite-width transformer model with MultiLayer Perceptron (MLP)

arXiv:2604.26514v1 Announce Type: cross Abstract: This paper investigates efficient methods for utilizing text-only data to improve speech recognition, focusing on encoder-dominated models that facili

arXiv:2604.26489v1 Announce Type: new Abstract: DNNs have gained widespread adoption in feature interaction recommendation models. However, there has been a longstanding debate on their roles. On one

arXiv:2604.24999v1 Announce Type: new Abstract: Thoracic Computed Tomography (CT) scans offer detailed insights into the intricate branching network of the airway tree, which is essential for understa

LangChain is offering multiple harness variants that are custom-fitted to specific use cases and models, recognizing that effective harness implementation requires tailored configuration rather than o