Search: “models”

DCEO: Direct Causal Effect Optimization for Long-Term User Value Modeling in E-commerce Search

arXiv:2608.25635v1 Announce Type: new Abstract: Industrial e-commerce search systems ultimately aim to optimize the user-level long-term objective, such as n-day cumulative purchases or gross merchand

safetyarxiv-cs-lg

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E2Rank: Unifying Text Embedding and Listwise Reranking for Effective and Efficient Search

DGX agent

arXiv:2510.22733v3 Announce Type: replace Abstract: Text embedding models deliver competitive retrieval performance with high efficiency, but their ranking fidelity remains limited compared to LLM-bas

model-releasesarxiv-cs-cl

27 Aug 2026

Local LLM harness for reverse engineering software?

Does anyone know of a decent reverse engineering harness/workspace setup for local models that I can just point the model at and have it go to work until it's reversed most if not all of the functions

Mitigating LLM sycophancy with RL-based fine-tuning: Bayesian Truth Serum approach

arXiv:2608.25267v1 Announce Type: new Abstract: Large language models (LLMs) frequently exhibit sycophancy: they adapt their answers to a user's stated beliefs or preferences instead of reporting what

Refusal geometry reflects refusal training: diverse refusal prefixes can raise stable rank and weaken refusal vector ablation attacks

arXiv:2608.25390v1 Announce Type: new Abstract: Refusal training protects AI models from jailbreaks by training models to decline unsafe queries, reducing the risk of misuse. Recent work finds that re

safetyarxiv-cs-lg

Running local LLM's as agents in Claude Code

I hit my token limit three times a day on my max subscription - got sick of that and designed this MCP setup to shift some of the coding load to my local Qwen3.8-27B model. I've been iterating on it n

SHIFT-LLM: Distribution Shift Correction in Depth-Pruned LLMs

arXiv:2608.25068v1 Announce Type: new Abstract: Depth pruning removes entire Transformer blocks to reduce the inference cost of large language models, but disrupts the hidden-state distributions expec

Theoretically Principled Federated Learning for Balancing Privacy and Utility

arXiv:2305.15148v3 Announce Type: replace Abstract: We propose a general learning framework for the protection mechanisms that protects privacy via distorting model parameters, which facilitates the t

We’re the Team Behind Apodex 1.1 — Ask Us Anything!

Hi r/LocalLLaMA ! We’re Apodex, the team behind Apodex 1.1, our new model family built to scale agentic intelligence for complex work. We’re excited to be here and answer your questions directly. Apod

Agents

When Obstacles Bend: Modeling Vegetation Deformation in the context of Field Robotics

arXiv:2608.26050v1 Announce Type: new Abstract: Autonomous robots operating in natural environments must often interact with vegetation rather than simply avoid it. In this context, traversability is

agentsarxiv-cs-ro

When RAG Fails to Equalize: Geo-bias in Factual Question Answering over Public Companies

model-releasesarxiv-cs-cl

arXiv:2608.25717v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is widely assumed to mitigate factual errors in large language models (LLMs), but it remains unclear whether retrie

Research

A Structural FHMM for Interpretable Disease Trajectories in T2DM

arXiv:2608.24328v1 Announce Type: new Abstract: In this work, we propose a structural variant of the Factorial Hidden Markov Model (FHMM) for the analysis of disease trajectories in patients with Type

researcharxiv-cs-lg

BenchBench-Protocol: Evaluating Real-World Wet-Lab Protocol Reasoning and Modification

arXiv:2608.23898v1 Announce Type: new Abstract: We introduce BenchBench-Protocol, a benchmark for large language models of 149 protocol-modification tasks recovered from modifications that scientists

EMRB: A Multi-Level Benchmark for Evaluating LLM Reasoning over Raw Electromagnetic Signals

arXiv:2608.24086v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as code agents for scientific and engineering analysis, but their ability to analyze raw physical-lay

Fully quantized NVFP4 Qwen3.8-27B with QUASAR QAD

We're releasing a fully quantized NVFP4 version of Qwen3.8-27B. The checkpoint was trained using quantization-aware distillation (QAD) with QUASAR, our new QAT algorithm. We used the original BF16 mod

Applications

Generating Intervention Hypotheses using Explainable Explanations on Graphs: G2I, a Two-Stage Greedy Framework

arXiv:2608.23835v1 Announce Type: new Abstract: Real-world decision-making in public health and social science can greatly benefit from predictive models, yet translating predictions into effective in

applicationsarxiv-cs-lg

Help on running Claude Code using ollama

Hi everyone. I am currently using gemma 4 model and used qwen 3:8b model. My goal is to use claude code to make projects, AI Tools Please help me find out what is more useful. Suppose i have to make a

model-releasesr-ollama

(Mis)Understanding Benign Overfitting in Equity Return Prediction

arXiv:2608.23761v1 Announce Type: cross Abstract: Highly overparameterized models often predict well despite interpolating training data in complex domains, challenging the classical bias--variance tr

NeuronTune: Fine-Grained Neuron Modulation for Balanced Safety-Utility Alignment in LLMs

arXiv:2508.09473v2 Announce Type: replace-cross Abstract: Ensuring robust safety alignment while preserving utility is critical for the reliable deployment of Large Language Models (LLMs). However, cu

safetyarxiv-cs-ai

Object Counting Across Modalities: Taxonomies, Benchmarks, Applications, and Open Challenges

arXiv:2608.23845v1 Announce Type: new Abstract: Object-counting methods have rapidly shifted from class-specific density regression to open-vocabulary, foundation-model-backed counters. These methods

On the https://Z.ai Code Bench, which measures real-world coding performance, GLM-5.3-Flash clearly outperforms GLM-5.2 at every effort leve…

model-releaseszhipu-ai--x

On August 26, 2026 Z.ai reported that its Code‑Bench metric—which assesses real‑world coding performance—shows GLM‑5.3‑Flash outperforming GLM‑5.2 at every effort level. The new model’s results are on

Parason: Revealing Subtask and Trial Parallelism in LLM Reasoning

arXiv:2608.24658v1 Announce Type: new Abstract: Scaling test-time reasoning has substantially improved the problem-solving ability of large language models (LLMs), but standard autoregressive decoding

PROOF-Gen: From Optimized Data to Better Distillation

arXiv:2608.23911v1 Announce Type: new Abstract: Supervised fine-tuning on teacher-generated trajectories is the standard first stage for distilling tool-calling capabilities into deployable models. Po

QML for Quantum Sensing under Measurement-Induced Information Loss

arXiv:2608.23934v1 Announce Type: cross Abstract: Nitrogen-vacancy (NV) centers in diamond can serve as highly sensitive solid-state quantum sensors for high-sensitivity magnetometry. However, in the

The inside story on why OpenAI agents hacked Hugging Face

model-releasesmit-tech-review

The models responsible for last month’s agent hack of Hugging Face had been inadvertently trained to cheat and to communicate with each other, according to an OpenAI technical report released today. T

AdaptPrompt: Parameter-Efficient Adaptation of VLMs for Generalizable Deepfake Detection

arXiv:2512.17730v2 Announce Type: replace Abstract: Detectors of AI-generated images tend to inherit the biases of the data they are trained on: models fitted to GAN imagery learn to treat GAN-specifi

Anchoring Bias: A Persistent Fairness Backdoor Attack against MLLMs under Continual Learning

arXiv:2608.21577v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in high-stakes domains where fairness is a critical safety requirement. In practice

Benchmarking and Boosting Multilingual Capabilities of LVLMs via OCR-Centric Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2503.18484v3 Announce Type: replace-cross Abstract: Evaluating the multilingual capabilities of Large Vision-Language Models (LVLMs) remains challenging because most benchmarks rely on non-paral

Research

Beyond Observed Auxiliary Relations: Environment-Conditioned Modeling for Multi-Behavior Recommendation

arXiv:2608.22920v1 Announce Type: new Abstract: Multi-behavior recommendation (MBR) leverages auxiliary behavioral signals, such as clicks and add-to-cart, to enhance target behavior prediction like p

researcharxiv-cs-ai

BioMed-Agent-RL: A Meta Learning, All You Need for Biomedical Applications

arXiv:2608.21864v1 Announce Type: cross Abstract: The current progress of Clinical Vision Large Language Models (C-VLLMs) has substantially improved digital diagnostics, still these frameworks often e

Context as an Environment: Programmatic Context Management for Long-Horizon Agents

arXiv:2608.21690v1 Announce Type: new Abstract: LLM agents increasingly take on long-running tasks whose history grows far beyond a single model context window. Existing approaches compress earlier in

DeltaGNN: Graph Neural Network with Information Flow Control

arXiv:2501.06002v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) are popular deep learning models designed to process graph-structured data through recursive neighborhood aggregations

Dual-Layer Agentic Memory with Fast Write Routing and Slow Consolidation

model-releasesarxiv-cs-cl

arXiv:2608.22215v1 Announce Type: new Abstract: Large language model (LLM) agents operate in dynamic environments where knowledge continuously evolves. Existing memory systems typically treat external

Evaluating Multimodal Narrative Understanding of Popular Hollywood Films

arXiv:2608.21430v1 Announce Type: new Abstract: Multimodal language models increasingly show promise for enabling the large-scale computational analysis of film, opening up new avenues for learning ab

Evaluating the Efficacy of LLMs to Emulate Realistic Human Personalities

arXiv:2402.14879v2 Announce Type: replace-cross Abstract: To enhance immersion and engagement in video games, the design of Affective Non-Player Characters (ANPCs) is a key focus for researchers and p

FigmaTrace: Capturing Creative Nuances in Human Figma Design Workflows

arXiv:2608.21460v1 Announce Type: cross Abstract: Vision Language Models have recently shown improvements in several objective and verifiable domains such as object detection but continue to underperf

From Inertia to Objectivity: Improving Deep Research Agents with Noise Isolation

arXiv:2608.23045v1 Announce Type: new Abstract: Web search agents powered by Large Language Models (LLMs) show strong promise, but deep research tasks expose a recurring failure mode: once an agent ha

Model-Based Reinforcement Learning for Heterogeneous Multi-Robot Task Assignment Under Distribution Shifts

arXiv:2608.21554v1 Announce Type: cross Abstract: Heterogeneous multi-robot service systems must assign requests to compatible robots, construct feasible schedules, and adapt as new tasks arrive onlin

safetyarxiv-cs-lg

New: Llama.cpp adaptive speculation for faster inference

We have been working on some performance optimisations for Qwen3.8 and other models. The main new feature that we introduced is adaptive speculation for Llama.cpp What is it? MTP and DFlash work well

OVIBench: Benchmarking Online Video Question Answering under Interruption

arXiv:2608.22279v1 Announce Type: cross Abstract: Recent vision language models (VLMs) have achieved strong progress in video understanding. However, most existing video QA research and benchmarks sti

Hardware

Prime Agent: A Self-Improving RLM Harness

arXiv:2608.23552v1 Announce Type: new Abstract: Language models are sequential processors, but long-horizon agency requires external information and computation beyond model weights and active context

hardwarearxiv-cs-ai

Redteaming Leading Arabic LLMs with ASAS

arXiv:2608.21985v1 Announce Type: new Abstract: As the adoption of large language models (LLMs) grows in Arabic-speaking regions, ensuring their safety and cultural alignment is increasingly critical.

Stress Testing Unlearning Algorithms

arXiv:2608.22527v1 Announce Type: new Abstract: Recently, machine unlearning, the removal of specific training data influence from a model, has gained increasing attention. In large language models (L

Your AI, On a Dial: Controlling Investment Bias in LLMs with a Single Neuron

arXiv:2608.22852v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in investment decision-making, yet prior work shows that they exhibit systematic, model-specific inve

safetyarxiv-cs-ai

ZOTTA: Test-Time Adaptation with Gradient-Free Zeroth-Order Optimization

arXiv:2603.14254v2 Announce Type: replace Abstract: Test-time adaptation (TTA) aims to improve model robustness under distribution shifts by adapting to unlabeled test data, but most existing methods

A Critical Audit of Spatiotemporal Forecasting Benchmark Datasets and Baselines

arXiv:2608.20980v1 Announce Type: new Abstract: Graph neural networks (GNNs) are routinely employed for short-range forecasting on multivariate time series with a spatial graph structure. Despite the

24 Aug 2026

ClawSentry: A Progressive Multi-Tier Security Monitor for Safeguarding Autonomous LLM Agents

arXiv:2608.21101v1 Announce Type: cross Abstract: As large language model (LLM) agents move from conversation to executing code, reading local files, and orchestrating external tools, a single agent h

24 Aug 2026

Applications

FF-MPCC: High-speed Agile Formation Flight with Model Predictive Contouring Control