Search: “models”

Cross-Lingual Attention Distillation with Personality-Informed Generative Augmentation for Multilingual Personality Recognition

arXiv:2604.08851v1 Announce Type: new Abstract: While significant work has been done on personality recognition, the lack of multilingual datasets remains an unresolved challenge. To address this, we

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Research

Detecting Diffusion-generated Images via Dynamic Assembly ForestsDetecting Diffusion-generated Images via Dynamic Assembly Forests

DGX agent

arXiv:2604.09106v1 Announce Type: new Abstract: Diffusion models are known for generating high-quality images, causing serious security concerns. To combat this, most efforts rely on deep neural netwo

researcharxiv-cs-cv

13 Apr 2026

Do LLMs Follow Their Own Rules? A Reflexive Audit of Self-Stated Safety Policies

arXiv:2604.09189v1 Announce Type: cross Abstract: LLMs internalize safety policies through RLHF, yet these policies are never formally specified and remain difficult to inspect. Existing benchmarks ev

safetyarxiv-cs-ai

EGMOF: Efficient Generation of Metal-Organic Frameworks Using a Hybrid Diffusion-Transformer Architecture

arXiv:2511.03122v2 Announce Type: replace-cross Abstract: Designing materials with targeted properties remains challenging due to the vastness of chemical space and the scarcity of property-labeled da

researcharxiv-cs-ai

EMA Is Not All You Need: Mapping the Boundary Between Structure and Content in Recurrent Context

arXiv:2604.08556v1 Announce Type: cross Abstract: What exactly do efficient sequence models gain over simple temporal averaging? We use exponential moving average (EMA) traces, the simplest recurrent

Envisioning the Future, One Step at a Time

arXiv:2604.09527v1 Announce Type: cross Abstract: Accurately anticipating how complex, diverse scenes will evolve requires models that represent uncertainty, simulate along extended interaction chains

Exploiting Web Search Tools of AI Agents for Data Exfiltration

arXiv:2510.09093v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are now routinely used to autonomously execute complex tasks, from natural language processing to dynamic workflo

researcharxiv-cs-cl

From Paper to Program: Accelerating Quantum Many-Body Algorithm Development via a Multi-Stage LLM-Assisted Workflow

arXiv:2604.04089v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate code rapidly but remain unreliable for scientific algorithms whose correctness depends on structural

GRASP: Grounded CoT Reasoning with Dual-Stage Optimization for Multimodal Sarcasm Target Identification

arXiv:2604.08879v1 Announce Type: new Abstract: Moving beyond the traditional binary classification paradigm of Multimodal Sarcasm Detection, Multimodal Sarcasm Target Identification (MSTI) presents a

How does Chain of Thought decompose complex tasks?

arXiv:2604.08872v1 Announce Type: new Abstract: Many language tasks can be modeled as classification problems where a large language model (LLM) is given a prompt and selects one among many possible a

researcharxiv-cs-lg

I benchmarked Gemma4:e4b vs Gemma3:27B vs GPT-4o-mini vs Gemini 2.5 Flash on a Mac Mini M4 Pro 24gb — full results

A Reddit user on r/ollama conducted a hands-on benchmark comparing Gemma4:e4b (Google's compact ~4.5B effective-parameter edge model) against Gemma3:27B, GPT-4o-mini, and Gemini 2.5 Flash, all run or

model-releasesr-ollama

Low-Data Supervised Adaptation Outperforms Prompting for Cloud Segmentation Under Domain Shift

arXiv:2604.08956v1 Announce Type: new Abstract: Adapting vision-language models to remote sensing imagery presents a fundamental challenge: both the visual and linguistic distributions of satellite da

Low Rank Based Subspace Inference for the Laplace Approximation of Bayesian Neural Networks

model-releasesarxiv-cs-lg

arXiv:2502.02345v2 Announce Type: replace Abstract: Subspace inference for neural networks assumes that a subspace of their parameter space suffices to produce a reliable uncertainty quantification. I

Memory-efficient Continual Learning with Prototypical Exemplar Condensation

arXiv:2603.13804v2 Announce Type: replace-cross Abstract: Rehearsal-based continual learning (CL) mitigates catastrophic forgetting by maintaining a subset of samples from previous tasks for replay. E

Memory-Efficient Transfer Learning with Fading Side Networks via Masked Dual Path Distillation

arXiv:2604.09088v1 Announce Type: new Abstract: Memory-efficient transfer learning (METL) approaches have recently achieved promising performance in adapting pre-trained models to downstream tasks. Th

Neural networks for Text-to-Speech evaluation

arXiv:2604.08562v1 Announce Type: cross Abstract: Ensuring that Text-to-Speech (TTS) systems deliver human-perceived quality at scale is a central challenge for modern speech technologies. Human subje

Predicting Metabolic Dysfunction-Associated Steatotic Liver Disease using Machine Learning Methods: A Retrospective Cohort Study

arXiv:2510.22293v4 Announce Type: replace Abstract: Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects 30-40% of US adults and is the most common chronic liver diseas

safetyarxiv-cs-lg

QuanBench+: A Unified Multi-Framework Benchmark for LLM-Based Quantum Code Generation

arXiv:2604.08570v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used for code generation, yet quantum code generation is still evaluated mostly within single frameworks

See you this Wednesday at the Ollama Gemma Meetup! 💎

Ollama announced a meetup focused on Gemma, Google's open-weight language model family, scheduled for Wednesday. The event likely brought together developers and AI enthusiasts to explore running Gemm

model-releasesollama--x

SPASM: Stable Persona-driven Agent Simulation for Multi-turn Dialogue Generation

arXiv:2604.09212v1 Announce Type: new Abstract: Large language models are increasingly deployed in multi-turn settings such as tutoring, support, and counseling, where reliability depends on preservin

Structured Exploration and Exploitation of Label Functions for Automated Data Annotation

arXiv:2604.08578v1 Announce Type: cross Abstract: High-quality labeled data is critical for training reliable machine learning and deep learning models, yet manual annotation remains costly and error-

researcharxiv-cs-ai

Structured Uncertainty guided Clarification for LLM Agents

arXiv:2511.08798v2 Announce Type: replace-cross Abstract: LLM agents with tool-calling capabilities often fail when user instructions are ambiguous or incomplete, leading to incorrect invocations and

Temporal Patch Shuffle (TPS): Leveraging Patch-Level Shuffling to Boost Generalization and Robustness in Time Series Forecasting

arXiv:2604.09067v1 Announce Type: new Abstract: Data augmentation is a crucial technique for improving model generalization and robustness, particularly in deep learning models where training data is

local-aiarxiv-cs-lg

Agents

There's a speed and focus tradeoff when building a core product and just using a frontier model/harness, but this is a pretty compelling arg…

Harrison Chase discusses the tradeoff between speed and focus when building a core product using a frontier model versus developing more customized solutions. Using a frontier model with a standard ha

agentsharrison-chase--x

TRU: Targeted Reverse Update for Efficient Multimodal Recommendation Unlearning

arXiv:2604.02183v2 Announce Type: replace Abstract: Multimodal recommendation systems (MRS) jointly model user-item interaction graphs and rich item content, but this tight coupling makes user data di

Benchmark Your Local LLMs in 3 Commands

This r/ollama post describes a streamlined method for performance-testing locally-running large language models using the Ollama framework, achievable with just three terminal commands. It likely intr

model-releasesr-ollama

Harness, Memory, Context Fragments, & the Bitter Lesson this is a work in progress mental dump on interesting intersections between how we u…

model-releasesharrison-chase--x

Harness, Memory, Context Fragments, & the Bitter Lesson this is a work in progress mental dump on interesting intersections between how we use and design a harness, implications for memory being accum

I built a VS Code extension that cuts my Claude API bill to ~$5/day

A developer shared on r/ollama how they built a custom VS Code extension that routes Claude API requests through locally-run models via Ollama, dramatically reducing cloud API costs to approximately $

model-releasesr-ollama

Hardware

MiniMax M2.7 Advances Scalable Agentic Workflows on NVIDIA Platforms for Complex AI Applications

MiniMax M2.7 is an enhancement of the MiniMax M2.5 model, built as a 230B-parameter Mixture-of-Experts (MoE) model with 10B active parameters per token and a 200K context length, designed for agentic

hardwarenvidia-developer

Tools

Run it on the AI Native Cloud — serverless and dedicated infrastructure. https://www.together.ai/models/minimax-m2-7

MiniMax-M2 is a large-scale mixture-of-experts (MoE) language model available for inference on Together AI's platform, accessible via both serverless and dedicated infrastructure options. The model ca

toolstogether-ai--x

Hallucination problem

A Reddit thread in r/ollama where a user reports experiencing AI hallucination issues when running local language models through Ollama. The discussion likely covers symptoms such as models generating

local-air-ollama

“Maybe I should try Chat again after only using Claude for a while”. First response:

I was unable to retrieve the specific Reddit thread content from that URL through my search. Reddit threads often require direct access to load user-generated content, and the search did not return...

model-releasesr-chatgpt

Open Everything 🤝 Own your intelligence 🤝 Builder Choice We’re in the v0.1 of deploying agentic intelligence across the economy. Agents ar…

model-releasesharrison-chase--x

Open Everything 🤝 Own your intelligence 🤝 Builder Choice We’re in the v0.1 of deploying agentic intelligence across the economy. Agents are data generating beasts! Experiential Memory: Each piece of g

OpenClaw + Ollama + gemma4:26b is fast in raw Ollama, but first heavy OpenClaw turns are extremely slow or hit idle timeout

Users running OpenClaw with `gemma4:26b` via Ollama encounter significantly slow or timed-out first turns in a session, even though the model responds quickly when queried directly through raw Olla...

local-air-ollama

ADAG: Automatically Describing Attribution Graphs

arXiv:2604.07615v1 Announce Type: new Abstract: In language model interpretability research, extbf{circuit tracing} aims to identify which internal features causally contributed to a particular outp

AgentOpt v0.1 Technical Report: Client-Side Optimization for LLM-Based Agent

arXiv:2604.06296v1 Announce Type: cross Abstract: AI agents are increasingly deployed in real-world applications, including systems such as Manus, OpenClaw, and coding agents. Existing research has pr

AVGen-Bench: A Task-Driven Benchmark for Multi-Granular Evaluation of Text-to-Audio-Video Generation

arXiv:2604.08540v1 Announce Type: cross Abstract: Text-to-Audio-Video (T2AV) generation is rapidly becoming a core interface for media creation, yet its evaluation remains fragmented. Existing benchma

Cannot search pdf document using WebUI and Ollama

Users in the Ollama/Open WebUI community commonly report being unable to query PDF documents via the Open WebUI interface when using a locally hosted Ollama backend, with the model failing to recog...

local-air-ollama

Chunks as Arms: Multi-Armed Bandit-Guided Sampling for Long-Context LLM Preference Optimization

arXiv:2508.13993v2 Announce Type: replace Abstract: Long-context modeling is critical for a wide range of real-world tasks, including long-context question answering, summarization, and complex reason

ClawsBench: Evaluating Capability and Safety of LLM Productivity Agents in Simulated Workspaces

arXiv:2604.05172v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly deployed to automate productivity tasks (e.g., email, scheduling, document management), but evalu

Tutorials

Cross-Modal Emotion Transfer for Emotion Editing in Talking Face Video

arXiv:2604.07786v1 Announce Type: new Abstract: Talking face generation has gained significant attention as a core application of generative models. To enhance the expressiveness and realism of synthe

tutorialsarxiv-cs-cv

Drift-Based Policy Optimization: Native One-Step Policy Learning for Online Robot Control

arXiv:2604.03540v2 Announce Type: replace Abstract: Although multi-step generative policies achieve strong performance in robotic manipulation by modeling multimodal action distributions, they require

safetyarxiv-cs-ro

DSCA: Dynamic Subspace Concept Alignment for Lifelong VLM Editing

arXiv:2604.07965v1 Announce Type: new Abstract: Model editing aims to update knowledge to add new concepts and change relevant information without retraining. Lifelong editing is a challenging task, p

EditCaption: Human-Aligned Instruction Synthesis for Image Editing via Supervised Fine-Tuning and Direct Preference Optimization

arXiv:2604.08213v1 Announce Type: new Abstract: High-quality training triplets (source-target image pairs with precise editing instructions) are a critical bottleneck for scaling instruction-guided im

Efficient and Effective Internal Memory Retrieval for LLM-Based Healthcare Prediction

arXiv:2604.07659v1 Announce Type: new Abstract: Large language models (LLMs) hold significant promise for healthcare, yet their reliability in high-stakes clinical settings is often compromised by hal

Efficient PRM Training Data Synthesis via Formal Verification

arXiv:2505.15960v3 Announce Type: replace Abstract: Process Reward Models (PRMs) have emerged as a promising approach for improving LLM reasoning capabilities by providing process supervision over rea

researcharxiv-cs-cl

Explainable AI to Improve Machine Learning Reliability for Industrial Cyber-Physical Systems

arXiv:2601.16074v2 Announce Type: replace Abstract: Industrial Cyber-Physical Systems (CPS) are sensitive infrastructure from both safety and economics perspectives, making their reliability criticall

safetyarxiv-cs-lg

FIT: A Large-Scale Dataset for Fit-Aware Virtual Try-On

arXiv:2604.08526v1 Announce Type: new Abstract: Given a person and a garment image, virtual try-on (VTO) aims to synthesize a realistic image of the person wearing the garment, while preserving their