Search: “models”

Interpreting Control Latents for System Identification via Conditional Flow Matching

arXiv:2608.23887v1 Announce Type: new Abstract: Latent-conditioned adaptive policies can control robots across changing dynamics, but their learned latents remain internal representations of the polic

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Safety

Latent Dynamics-Aware OOD Monitoring for Trajectory Prediction with Provable Guarantees

DGX agent

arXiv:2603.14603v2 Announce Type: replace Abstract: In safety-critical Cyber-Physical Systems (CPS), trajectory prediction guides downstream planning and control. Deep learning models forecast well on

safetyarxiv-cs-ro

26 Aug 2026

LumiXAI: A Modular Full-Stack Framework for Feature Attribution

arXiv:2608.24524v1 Announce Type: cross Abstract: Feature attribution is a central tool of model interpretability, yet the software through which it is applied remains fragmented: individual tools spe

Memory Is Not Always Needed: Characterizing Conditional Memory in Scientific Reasoning

arXiv:2608.23982v1 Announce Type: new Abstract: Scientific reasoning requires language models to retrieve specialized knowledge and incorporate it reliably into multi-step computation. Conditional mem

MetaRAG: Belief-Action Aligned Policy Optimization for Agentic RAG

arXiv:2608.24214v1 Announce Type: new Abstract: Agentic retrieval-augmented generation (RAG) requires language models to decide when to continue searching and when to answer. Existing RL-based methods

safetyarxiv-cs-ai

Industry

METR and Redwood detail how ~1,200 OpenAI agents coordinated cheating on an unsanctioned board, sending 70K+ messages and files, and ~700 attacked Hugging Face (METR)

METR: METR and Redwood detail how ~1,200 OpenAI agents coordinated cheating on an unsanctioned board, sending 70K+ messages and files, and ~700 attacked Hugging Face — Redaction summary statement: Exc

industrytechmeme

MoE-based Feature Adapter for Prompt-free Binary Coronary Artery Segmentation in X-ray Angiography

model-releasesarxiv-cs-cv

arXiv:2608.24783v1 Announce Type: new Abstract: Accurate segmentation of coronary arteries in X-ray angiography videos is essential for quantitative coronary analysis and image-guided interventions. H

MoRF-AST: Calibrated Probabilistic Virtual Sensing for Structural Monitoring under Changing Operating Conditions

arXiv:2608.24531v1 Announce Type: cross Abstract: Probabilistic full-field reconstruction provides uncertainty-aware response evidence for structural reliability assessment, yet inference from sparse

NeuronGuard: Robust LLM Safety Alignment via Ablation-Aware Safety Signal Redistribution

arXiv:2608.23959v1 Announce Type: cross Abstract: Safety alignment in large language models (LLMs) remains brittle against a growing spectrum of attacks. Jailbreak attacks bypass safety mechanisms thr

safetyarxiv-cs-ai

No reward hacking was found in GLM-5.2: solve the task, not the benchmark.

No reward hacking was found in GLM-5.2: solve the task, not the benchmark. Introducing reward hacking score corrections to the Artificial Analysis Coding Agent Index In v1.4 of the Artificial Analysis

model-releasesollama--x

Paritok-4B: Intent-Conditioned Context Compression for Coding Agents

arXiv:2608.24188v1 Announce Type: new Abstract: Coding agents re-send large file reads and tool outputs to a frontier LLM every turn, and this context dominates their token bill. General-purpose promp

PROOF-Gen: From Optimized Data to Better Distillation

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Supervised fine-tuning on teacher-generated trajectories is the standard first stage for distilling tool-calling capabilities into deployable models. Post-training pipelines that drive shipped tool-ca

QABBA: Error-Guaranteed Symbolic Time-Series Compression via Integer-Quantized Aggregation

arXiv:2411.15209v3 Announce Type: replace Abstract: The expansion of time-series data from sensors and monitoring systems has made compact representations increasingly important. Such representations

SA-Bench: Evaluating Semantic Alignment in LLM-Based Paper Reproduction

arXiv:2608.24252v1 Announce Type: new Abstract: LLM agents can generate paper reproduction code, yet often produce scientifically unfaithful implementations. We define this failure mode as semantic dr

SENSESHIFT: Continuous Sentiment-Controlled Text Generation via Encoder-based Mask Infilling

arXiv:2608.24304v1 Announce Type: cross Abstract: Recent controllable text generation (CTG) for sentiment control has largely focused on decoder-based large language models, making causal attention th

Sensorless damage-safe grasping

model-releasesarxiv-cs-ro

arXiv:2608.23983v1 Announce Type: new Abstract: Robotic fruit harvesting must hold produce securely without bruising it, yet compression stiffness varies several-fold with ripeness within a single spe

Source-Face Authenticity Detection for 3D Gaussian Heads Reconstructed from a Single Portrait: A Benchmark and Dedicated Detector

model-releasesarxiv-cs-cv

arXiv:2608.23984v1 Announce Type: new Abstract: Recent advances in single-image 3D Gaussian head reconstruction have enabled highly realistic and freely renderable digital heads from a single portrait

STAIN-FL: Stealthy Targeted Attack Injection with Contextual Triggers in Federated Learning

arXiv:2608.23952v1 Announce Type: cross Abstract: Federated video anomaly detection trains model collaboratively without sharing raw surveillance footage, but limited server-side visibility lets compr

Structured Frequency-Domain Evidence for LLM-Based Time-Series Anomaly Detection

arXiv:2608.24113v1 Announce Type: cross Abstract: Time-series anomalies can appear not only as pointwise deviations but also as changes in recurring temporal structure, such as shifted periodicity or

Syn2RealTrack: Bridging the Gap Between Synthetic and Real-World Datasets for Online Multi-View Multi-Target Tracking

arXiv:2608.24130v1 Announce Type: cross Abstract: Multi-camera 3D perception systems for warehouse scenes are trained largely on synthetic data and evaluated on physically captured environments. The r

TLXML: Task-Level Explanation of Meta-Learning via Influence Functions

arXiv:2501.14271v4 Announce Type: replace Abstract: Meta-learning enables models to rapidly adapt to new tasks by leveraging prior experience, but its adaptation mechanisms remain opaque, especially r

researcharxiv-cs-lg

Applications

TW-LegalBench: Measuring Taiwanese Legal Understanding

arXiv:2606.18699v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown impressive capabilities across diverse tasks, yet their performance on jurisdiction-specific legal rea

applicationsarxiv-cs-ai

v0.33.1

model-releasesollama-releases

What's Changed MLX: Qwen3.8 Flash Next support cmake: make external compat patches idempotent MLX and llama.cpp update mlxrunner: add structured output support mlxrunner: avoid Metal GPU timeouts when

we made Qwen 3.8 27b MLX vision quants and compared them against other popular community publishers (lm-studio, lukaskremla, mlx-community and etc)

model-releasesr-localllama

we made vision mlx quants of qwen3.8 27b (9 builds from 8bit at 29.5 GB down to 3.23bpw DWQ at 11.8 GB) and compared them against other community vision mlx quants from hf (we only compared vision bui

What FID Hides: Detecting, Ranking, and Diagnosing Deviations in Generative Evaluation

arXiv:2608.24881v1 Announce Type: cross Abstract: Generative models are commonly ranked by Frechet Inception Distance (FID) and Kernel Inception Distance (KID), yet FID's first-two-moment summary can

researcharxiv-cs-lg

With only 6B active parameters, Qwen3.8-Flash-Next-Base tops 8 of 14 benchmarks, including MMLU-Pro, SuperGPQA, BBH and GSM8K. And it remain…

With only 6B active parameters, Qwen3.8-Flash-Next-Base tops 8 of 14 benchmarks, including MMLU-Pro, SuperGPQA, BBH and GSM8K. And it remains competitive with Qwen3.7-Plus-Base on the rest. Its 51B N-

model-releasesqwen--x

A Multi-Domain and Multi-Task Generative Framework with Explicit Task and Domain Conditioning for Cross-Domain Event Extraction

arXiv:2608.23235v1 Announce Type: new Abstract: Event extraction aims to identify event triggers, classify event types, and extract arguments to construct structured event representations. Despite str

researcharxiv-cs-cl

A Query-Time Framework for Transient 2D Pore-Scale Flow Prediction and Generative Design

arXiv:2608.22235v1 Announce Type: new Abstract: Pore-scale flow governs transport and permeability behaviour in porous media engineering applications, yet repeated lattice Boltzmann method (LBM) simul

ADHint: Adaptive Hints with Difficulty Priors for Reinforcement Learning

model-releasesarxiv-cs-cv

arXiv:2512.13095v3 Announce Type: replace Abstract: To address the limited capability expansion and low sample efficiency of Reinforcement Learning (RL), recent methods have integrated ''hints'' into

Agents

AgentFlow: when the agent's workflow learns

For two years, the field has gotten very good at training models, and it still hand-wires the agents around them. Whether an agent plans, searches, calls a tool, or checks its own work before answerin

agentslambda-labs

Agents

Agentic Security: A Systematization of Tools, Failure Modes, and Design Laws for LLM-Driven Penetration Testing

arXiv:2608.21423v1 Announce Type: cross Abstract: Agentic security uses large-language-model (LLM) agents to plan, dispatch, and interpret security tools. As these systems move from demonstrations to

agentsarxiv-cs-ai

An offline approach to fNIRS-guided reinforcement learning for robot behavior

arXiv:2607.14393v2 Announce Type: replace-cross Abstract: Human-in-the-loop Reinforcement Learning has become a popular approach for training, finetuning, and aligning robot behavior with user prefere

Analyzing and Mitigating Cross-Lingual Degradation in Multilingual Medical VQA

arXiv:2608.22363v1 Announce Type: new Abstract: Medical visual question answering (VQA) is a crucial task in clinical AI, yet its evaluation has so far centered almost exclusively on English, limiting

AUDITA: certified auditing and causal attribution of adverse outcomes in autonomous multi-agent systems

arXiv:2608.22160v1 Announce Type: new Abstract: Physical automation is scaling toward fleets of embodied machines commanded by an AI brain. Early deployments already run factories and warehouses at pr

Beyond Dense Adam States: Adaptive Log-Space Quantization for Memory-Efficient Optimizers

arXiv:2608.22322v1 Announce Type: new Abstract: Low-precision optimizer-state methods are commonly designed for dense Adam-style moments, but memory-efficient optimizers maintain factored, confidence-

Beyond Sparse Weights: When Is Attention Compressible?

model-releasesarxiv-cs-cl

arXiv:2608.21541v1 Announce Type: cross Abstract: KV-cache compression is often justified by attention maps with a few large weights. This is incomplete: large weights may not contain most of the mass

Bi-EZP: LLM-Guided Bilevel Program Evolution for Ensemble Zero-Cost Proxy Discovery

arXiv:2608.21927v1 Announce Type: cross Abstract: Zero-cost proxies enable neural architecture search (NAS) to rank candidate networks from statistics computed at initialization, avoiding repeated tra

Bulbul: A Dataset for Dialectal Arabic Speech Recognition

arXiv:2608.21950v1 Announce Type: cross Abstract: Arabic automatic speech recognition (ASR) faces unique challenges due to diglossia, extensive regional dialect variation, and limited speech resources

ClawProBench: Trace-Aware Evaluation of AI Agents with Runtime Coverage and Frozen Workplace-Style Holdouts

arXiv:2608.22510v1 Announce Type: new Abstract: Agent benchmarks often evaluate only final answers even when agents run on stateful runtimes. We argue this under-specifies what is being evaluated: the

Cross-Subject Generalization in Decoding Perceived Speech from Non-Invasive Brain Recordings

arXiv:2608.22420v1 Announce Type: cross Abstract: Decoding perceived speech from non-invasive brain recordings has garnered significant attention in recent years due to its wide range of potential app

Deep Clustering Evaluation: How to Validate Internal Clustering Validation Measures

arXiv:2403.14830v2 Announce Type: replace-cross Abstract: Deep clustering partitions complex high-dimensional data using deep neural networks for clustering. It involves projecting data into lower-dim

DeepSAGE: Stage-Aware Reinforcement Learning for Structured CBT Counseling Dialogue

arXiv:2608.22615v1 Announce Type: new Abstract: Large Language Model (LLM)-based counseling agents can generate fluent and supportive responses, but they often lack the structured, goal-directed progr

safetyarxiv-cs-ai

Development and Feasibility Evaluation of an Edge AI as Medical Device System for Breast Cancer Multidisciplinary Team Meetings

arXiv:2608.22108v1 Announce Type: new Abstract: Breast Cancer Multidisciplinary Team (MDT) meetings manage increasingly complex cases under considerable time pressure, and documentation requirements c

DIAG: Diagnostic Iterative Alignment and Generation for Data-Efficient Mathematical Preference Distillation

arXiv:2608.22806v1 Announce Type: new Abstract: Iterative preference optimization is essential for aligning Large Language Models on mathematical reasoning tasks, yet its efficiency is often throttled

safetyarxiv-cs-cl

Divisive Normalization Shapes Low-Rank Slow Manifolds for Continuous Working Memory

arXiv:2608.01947v2 Announce Type: replace-cross Abstract: The ability to robustly maintain and update continuous variables is a hallmark of working memory. While classical continuous attractor network

Local Ai

DRBD-Mamba for Robust and Efficient Brain Tumor Segmentation with Analytical Insights

arXiv:2510.14383v4 Announce Type: replace Abstract: Accurate brain tumor segmentation is significant for clinical diagnosis and treatment but remains challenging due to tumor heterogeneity. Mamba-base

local-aiarxiv-cs-cv

DynaContext: Self-Improving Dynamic Contextualization of Optimized Prompts for Heterogeneous Parameter Extraction

arXiv:2608.22014v1 Announce Type: new Abstract: Automated prompt and skill optimization typically produces a single static instruction that is reused across inference instances until the next optimiza

EarthVerse: Benchmarking Scientific Agents Across Dynamic Earth Systems and Natural Hazards

arXiv:2608.23525v1 Announce Type: new Abstract: Earth-system analysis reconstructs changing physical processes from observations that differ in source, scale, timing, and modality. Natural hazards mak