Search: “models”

Parcae: Scaling Laws For Stable Looped Language Models

model-releasesarxiv-cs-lg

arXiv:2604.12946v1 Announce Type: new Abstract: Traditional fixed-depth architectures scale quality by increasing training FLOPs, typically through increased parameterization, at the expense of a high

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Point Prompting: Counterfactual Tracking with Video Diffusion Models

DGX agent

arXiv:2510.11715v2 Announce Type: replace Abstract: Trackers and video generators solve closely related problems: the former analyze motion, while the latter synthesize it. We show that this connectio

researcharxiv-cs-cv

15 Apr 2026

ResBM: Residual Bottleneck Models for Low-Bandwidth Pipeline Parallelism

arXiv:2604.11947v1 Announce Type: cross Abstract: Unlocking large-scale low-bandwidth decentralized training has the potential to utilize otherwise untapped compute resources. In centralized settings,

Siamese Foundation Models for Crystal Structure Prediction

arXiv:2503.10471v2 Announce Type: replace-cross Abstract: Predicting crystal structures from chemical compositions is a fundamental challenge in materials discovery, complicated by complex 3D geometri

tutorialsarxiv-cs-ai

WikiSeeker: Rethinking the Role of Vision-Language Models in Knowledge-Based Visual Question Answering

model-releasesarxiv-cs-cl

arXiv:2604.05818v2 Announce Type: replace-cross Abstract: Multi-modal Retrieval-Augmented Generation (RAG) has emerged as a highly effective paradigm for Knowledge-Based Visual Question Answering (KB-

A robust and adaptive MPC formulation for Gaussian process models

arXiv:2507.02098v2 Announce Type: replace-cross Abstract: In this paper, we present a robust and adaptive model predictive control (MPC) framework for uncertain nonlinear systems affected by bounded d

tutorialsarxiv-cs-lg

ASPIRin: Action Space Projection for Interactivity-Optimized Reinforcement Learning in Full-Duplex Speech Language Models

arXiv:2604.10065v1 Announce Type: cross Abstract: End-to-end full-duplex Speech Language Models (SLMs) require precise turn-taking for natural interaction. However, optimizing temporal dynamics via st

ChemPro: A Progressive Chemistry Benchmark for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2602.03108v3 Announce Type: replace Abstract: We introduce ChemPro, a progressive benchmark with 4100 natural language question-answer pairs in Chemistry, across 4 coherent sections of difficult

CoSToM:Causal-oriented Steering for Intrinsic Theory-of-Mind Alignment in Large Language Models

arXiv:2604.10031v1 Announce Type: cross Abstract: Theory of Mind (ToM), the ability to attribute mental states to others, is a hallmark of social intelligence. While large language models (LLMs) demon

DeCoVec: Building Decoding Space based Task Vector for Large Language Models via In-Context Learning

arXiv:2604.11129v1 Announce Type: new Abstract: Task vectors, representing directions in model or activation spaces that encode task-specific behaviors, have emerged as a promising tool for steering l

dTRPO: Trajectory Reduction in Policy Optimization of Diffusion Large Language Models

arXiv:2603.18806v2 Announce Type: replace Abstract: Diffusion Large Language Models (dLLMs) introduce a new paradigm for language generation, which in turn presents new challenges for aligning them wi

Local Ai

Fixed: IPEX-LLM + modern Ollama models (qwen3, gemma4) on Intel Arc 140V Lunar Lake Windows 11 — undocumented solution

This Reddit post from r/ollama documents a community-discovered, undocumented workaround for getting IPEX-LLM to successfully run modern Ollama models — specifically Qwen3 and Gemma4 — on systems powe

local-air-ollama

Revisiting Epistemic Markers in Confidence Estimation: Can Markers Accurately Reflect Large Language Models' Uncertainty?

arXiv:2505.24778v3 Announce Type: replace Abstract: As large language models (LLMs) are increasingly used in high-stakes domains, accurately assessing their confidence is crucial. Humans typically exp

safetyarxiv-cs-cl

RoboStereo: Dual-Tower 4D Embodied World Models for Unified Policy Optimization

arXiv:2603.12639v2 Announce Type: replace Abstract: Scalable Embodied AI faces fundamental constraints due to prohibitive costs and safety risks of real-world interaction. While Embodied World Models

safetyarxiv-cs-cv

SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models

arXiv:2604.10091v1 Announce Type: new Abstract: Large language models (LLMs) have shown remarkable performance in various domains, but they are constrained by massive computational and storage costs.

SMFormer: Empowering Self-supervised Stereo Matching via Foundation Models and Data Augmentation

model-releasesarxiv-cs-cv

arXiv:2604.10218v1 Announce Type: new Abstract: Recent self-supervised stereo matching methods have made significant progress. They typically rely on the photometric consistency assumption, which pres

Towards Reasonable Concept Bottleneck Models

arXiv:2506.05014v2 Announce Type: replace-cross Abstract: We propose a novel, flexible, and efficient framework for designing Concept Bottleneck Models (CBMs) that enables practitioners to explicitly

Enhancing the Safety of Medical Vision-Language Models by Synthetic Demonstrations

arXiv:2506.09067v2 Announce Type: replace-cross Abstract: Generative medical vision-language models~(Med-VLMs) are primarily designed to generate complex textual information~(e.g., diagnostic reports)

Grammar as a Behavioral Biometric: Using Cognitively Motivated Grammar Models for Authorship Verification

arXiv:2403.08462v3 Announce Type: replace Abstract: Authorship Verification (AV) is a key area of research in digital text forensics, which addresses the fundamental question of whether two texts were

Hermes Agent Tip💡 Hermes supports dedicated auxiliary models for eight task types: 1. vision 2. web_extract 3. compression 4. session_searc…

Hermes Agent Tip💡 Hermes supports dedicated auxiliary models for eight task types: 1. vision 2. web_extract 3. compression 4. session_search 5. approval 6. skills_hub 7. mcp 8. flush_memories Each tas

agentsnous-research--x

InsEdit: Towards Instruction-based Visual Editing via Data-Efficient Video Diffusion Models Adaptation

arXiv:2604.08646v1 Announce Type: new Abstract: Instruction-based video editing is a natural way to control video content with text, but adapting a video generation model into an editor usually appear

researcharxiv-cs-cv

Large Reasoning Models Learn Better Alignment from Flawed Thinking

arXiv:2510.00938v2 Announce Type: replace Abstract: Large reasoning models (LRMs) 'think' by generating structured chain-of-thought (CoT) before producing a final answer, yet they still lack the abili

safetyarxiv-cs-lg

Parameterized Complexity Of Representing Models Of MSO Formulas

model-releasesarxiv-cs-ai

arXiv:2604.08707v1 Announce Type: new Abstract: Monadic second order logic (MSO2) plays an important role in parameterized complexity due to the Courcelle's theorem. This theorem states that the probl

Local Ai

Tango: Taming Visual Signals for Efficient Video Large Language Models

arXiv:2604.09547v1 Announce Type: new Abstract: Token pruning has emerged as a mainstream approach for developing efficient Video Large Language Models (Video LLMs). This work revisits and advances th

local-aiarxiv-cs-cv

Token Reduction via Local and Global Contexts Optimization for Efficient Video Large Language Models

arXiv:2603.01400v2 Announce Type: replace Abstract: Video Large Language Models (VLLMs) demonstrate strong video understanding but suffer from inefficiency due to redundant visual tokens. Existing pru

researcharxiv-cs-cv

Industry

AI models are terrible at betting on soccer—especially xAI Grok

A report called 'KellyBench,' released by AI start-up General Reasoning, tested eight leading AI models in a virtual re-creation of the 2023–24 Premier League season, providing them with detailed hist

industryars-technica

11 Apr 2026

A systematic framework for generating novel experimental hypotheses from language models

arXiv:2408.05086v3 Announce Type: replace Abstract: Neural language models (LMs) have been shown to capture complex linguistic patterns, yet their utility in understanding human language and more broa

safetyarxiv-cs-cl

AFL: A Single-Round Analytic Approach for Federated Learning with Pre-trained Models

arXiv:2405.16240v3 Announce Type: replace Abstract: In this paper, we introduce analytic federated learning (AFL), a new training paradigm that brings analytical (i.e., closed-form) solutions to the f

researcharxiv-cs-lg

Industry

Apple's head of cloud says Open Source models will address 90% of the use case

I was unable to retrieve the specific Reddit thread or locate reliable sourced details about Apple's head of cloud making a statement that open source models will address 90% of use cases. The sear...

industryr-chatgpt

Attribution-Driven Explainable Intrusion Detection with Encoder-Based Large Language Models

arXiv:2604.06266v1 Announce Type: cross Abstract: Software-Defined Networking (SDN) improves network flexibility but also increases the need for reliable and interpretable intrusion detection. Large L

tutorialsarxiv-cs-ai

Energy-Regularized Spatial Masking: A Novel Approach to Enhancing Robustness and Interpretability in Vision Models

arXiv:2604.06893v1 Announce Type: cross Abstract: Deep convolutional neural networks achieve remarkable performance by exhaustively processing dense spatial feature maps, yet this brute-force strategy

researcharxiv-cs-lg

Flow Motion Policy: Manipulator Motion Planning with Flow Matching Models

model-releasesarxiv-cs-ai

arXiv:2604.07084v1 Announce Type: cross Abstract: Open-loop end-to-end neural motion planners have recently been proposed to improve motion planning for robotic manipulators. These methods enable plan

Hallucination as output-boundary misclassification: a composite abstention architecture for language models

arXiv:2604.06195v1 Announce Type: cross Abstract: Large language models often produce unsupported claims. We frame this as a misclassification error at the output boundary, where internally generated

Incentive-Aware Multi-Fidelity Optimization for Generative Advertising in Large Language Models

arXiv:2604.06263v1 Announce Type: cross Abstract: Generative advertising in large language model (LLM) responses requires optimizing sponsorship configurations under two strict constraints: the strate

LINE: LLM-based Iterative Neuron Explanations for Vision Models

arXiv:2604.08039v1 Announce Type: new Abstract: Interpreting the concepts encoded by individual neurons in deep neural networks is a crucial step towards understanding their complex decision-making pr

safetyarxiv-cs-cv

One Life to Learn: Inferring Symbolic World Models for Stochastic Environments from Unguided Exploration

arXiv:2510.12088v2 Announce Type: replace Abstract: Symbolic world modeling requires inferring and representing an environment's transitional dynamics as an executable program. Prior work has focused

agentsarxiv-cs-ai

The quality of talks at @aiDotEngineer is insane, being able to learn about diffusion models and flow mapping from @GoogleDeepMind’s @sediel…

The AI Engineer Summit (@aiDotEngineer) is a highly regarded technical conference featuring speakers from leading AI organizations including Google DeepMind, Anthropic, and OpenAI, known for its de...

tutorialsswyx--x

a useful mental model on how teams can think about good data design to improve their models/agents: Evals ~= Training Data ~= Environments -…

a useful mental model on how teams can think about good data design to improve their models/agents: Evals ~= Training Data ~= Environments - in Classical Deep Learning, we learn from each training exa

agentsharrison-chase--x

9 Apr 2026

Another banger paper from Microsoft. Why it's a big deal: It teaches reasoning models to compress their own chain-of-thought mid-generation.…

Another banger paper from Microsoft. Why it's a big deal: It teaches reasoning models to compress their own chain-of-thought mid-generation. The most interesting finding isn't the 2-3x memory savings

agentsdair-ai--x

9 Apr 2026

This 10-min read from @Vtrivedy10 changes how you build AI agents. Most people are stuck in the same loop; switching models when agents brea…

This 10-min read from @Vtrivedy10 changes how you build AI agents. Most people are stuck in the same loop; switching models when agents break. The reframe: evals are the training data for your harness

agentsharrison-chase--x

9 Apr 2026

What are the odds Qwen 4 models are going to think less?

model-releasesr-localllama

Qwen4s are hopefully coming pre-Xmas… there was all the announcements recently but no exact release date. I’m running qwen flash next 3.8 at about 28tokens per second and gotta be real, most of those

18 Oct 2026

CoSTA: Compressed Speech Token Adaptation for Efficient Spoken Dialogue Models

arXiv:2610.21143v1 Announce Type: cross Abstract: Spoken Dialogue Models (SDMs) typically share a speech-token space for generation and synthesis, leading to long autoregressive sequences and costly i

CoTS: Competitive Token Selection for Latent Reasoning in Large Language Models

arXiv:2610.20642v1 Announce Type: cross Abstract: Recent latent reasoning methods move beyond discrete Chain-of-Thought (CoT) by replacing sampled tokens with continuous soft embeddings or hidden stat

Diffusion Language Models as Open Quantum Systems

arXiv:2610.21672v1 Announce Type: cross Abstract: Diffusion language models generate text by reversing a classical diffusion process over token sequences. We show that their continuous-time forward an

Applications

LTM: Latent Transition Based In-Context Memory for Vision-Language-Action Models

arXiv:2610.21362v1 Announce Type: cross Abstract: Robotic manipulation often requires remembering interactions that are no longer visible. We introduce Latent Transition Memory (LTM), which stores his

applicationsarxiv-cs-ai

MindEval2: Clinically Grounded Patients and Rubrics for Evaluating Language Models in Mental Health Support

arXiv:2610.22314v1 Announce Type: new Abstract: With people increasingly turning to AI chatbots for mental health support, the need to evaluate these tools is becoming more pressing. Recent benchmarks

One Is Not Enough: How People Use Multiple AI Models in Everyday Life

arXiv:2603.26107v1 Announce Type: cross Abstract: People increasingly use multiple Multimodal Large Language Models (MLLMs) concurrently, selecting each based on its perceived strengths. This cross-pl

agentsarxiv-cs-ai

Realtime-Bench: Can Frontier Models Solve Real-time Interactive Problems?

arXiv:2610.22155v1 Announce Type: new Abstract: Real-time interaction requires agents to perceive evolving environments and act under temporal constraints, yet existing evaluations of real-time stream