Search: “model-releases”

Jailbreaking Open-Weight LLMs via Random Embedding Perturbations

arXiv:2610.07125v1 Announce Type: cross Abstract: While open-weight models have enjoyed steady progress in capabilities and wide adoption across multiple domains, their safety remains an important con

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Model Releases

JIVEAdapter: A Multi-Task Additive Low-Rank Adapter via Joint and Individual Variation Explained (JIVE)

DGX agent

arXiv:2610.07036v1 Announce Type: new Abstract: Parameter-efficient fine-tuning adapts pretrained models at a fraction of the cost of full fine-tuning, yet most low-rank adapters are single-task and r

model-releasesarxiv-cs-ai

7 Oct 2026

JudgeMoE: Distributional Aggregation for LLM-as-a-Judge

arXiv:2610.07109v1 Announce Type: new Abstract: When an LLM judge scores an output, its score distribution retains uncertainty and disagreement information that is lost after scalar compression. We in

Knee3DVLM: Dual-Sequence Full-Volume Vision-Language Modeling for Comprehensive Knee MRI Assessment

arXiv:2610.08482v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly being applied to three-dimensional medical imaging, but their application to knee MRI remains limited,

Knowing When Not to Answer: Cross-Domain and Multi-Turn Generalization of Latent Underspecification Signals

arXiv:2610.08413v1 Announce Type: cross Abstract: Large language models routinely answer questions that cannot be answered from the information given, and in dialogue they answer before enough has bee

KO: Kinetics-inspired Neural Optimizer with PDE Simulation Approaches

arXiv:2505.14777v2 Announce Type: replace-cross Abstract: The design of effective optimization algorithms for neural networks remains a fundamental challenge, and most existing methods rely on heurist

Label-Efficient Deep Learning for ECG Delineation: A Multi-Dataset Benchmark against Widely Used Delineation Tools

arXiv:2610.07885v1 Announce Type: cross Abstract: Electrocardiogram (ECG) delineation, the identification of waveform boundaries, is a foundational step that translates raw ECG signals into clinically

Language Unalignability: Why Some Concepts Resist Cross-Cultural Benchmark Evaluation

arXiv:2610.08303v1 Announce Type: new Abstract: Current evaluation of multilingual Large Language Models (LLMs) rests on an implicit Translation-Isomorphism Assumption (TIA): that semantic structures

Large Pretraining Datasets Don't Guarantee Robustness after Fine-Tuning in Image Classification

arXiv:2410.21582v4 Announce Type: replace-cross Abstract: Large-scale pretrained models are widely leveraged as foundations for learning new specialized tasks via fine-tuning, with the goal of maintai

Later Is Better: Token Reduction for ViTs Under Distribution Shift

arXiv:2610.07758v1 Announce Type: cross Abstract: Training-free token reduction accelerates vision transformers by removing redundant tokens across layers, recovering most of the original accuracy at

LeanPlan: Optimal Planning with LLM-Generated Heuristics and Admissibility Proofs

arXiv:2610.08246v1 Announce Type: new Abstract: Frontier large language models (LLMs) can generate heuristic functions that guide search to achieve state-of-the-art performance in satisficing planning

LEAP: Making Privileged Geometry Supervision Effective for Visuomotor Learning

arXiv:2610.07015v1 Announce Type: new Abstract: Privileged 3D supervision uses additional geometric information during training to guide RGB-based visuomotor policy learning, without requiring geometr

Learn2Play Bench: How Well Do LLM Agents Learn from Experience in Unfamiliar Environments?

arXiv:2610.08215v1 Announce Type: new Abstract: Learning from experience is essential for LLM agents to adapt to unfamiliar and dynmaic environments. Evaluating this ability is therefore important for

Learned Adaptive Multiresolution Diffusion Imaging

arXiv:2610.07884v1 Announce Type: cross Abstract: Adaptive multiresolution methods reduce representation cost by concentrating fine-scale degrees of freedom where needed, but their tree updates are us

Learning Decision-Stump Thresholds in Context: Dynamics of Softmax Attention

arXiv:2610.07074v1 Announce Type: cross Abstract: Estimating a decision threshold requires locating observations near an unknown boundary. We study how gradient-based pretraining learns this statistic

Learning to Decide, Not to Reason: Parameter-Efficient Decision Operators via Low-Rank Activation Steering

arXiv:2610.06950v1 Announce Type: cross Abstract: Injecting skills into a frozen language model currently costs a million parameters and a reinforcement-learning pipeline. We introduce method{}, a Sys

Learning to Outgrow a Theory: Experimental Discovery Beyond the Initial Hypothesis Space

arXiv:2610.07627v1 Announce Type: new Abstract: Scientific discovery systems typically optimize experiments within a fixed hypothesis space. This creates a failure mode when all available candidates o

Learning to Remember: Distilling Memory Retention for Compact Recurrent Neural Networks

arXiv:2610.06942v1 Announce Type: new Abstract: Deep learning models, particularly recurrent neural networks and their variants, such as long short-term memory, have significantly advanced time series

Learning to Retrieve via Reinforcement Learning in Embedding Space

arXiv:2610.07731v1 Announce Type: cross Abstract: Dense retrieval models are typically trained with contrastive objectives that learn effective representations but do not directly optimize retrieval m

Learning When to Refine: Long-Horizon Reinforcement Learning for Budgeted Neural-Operator PDE Solvers

arXiv:2610.06883v1 Announce Type: cross Abstract: Neural operators provide fast surrogates for time-dependent PDEs, but autoregressive deployment creates a refinement-allocation problem: prediction er

Lego-Like Stiffness Configuration of Planar Compliant Modules for Task-Specific Flexible Interfaces

arXiv:2610.07319v1 Announce Type: new Abstract: Compliant mechanisms provide compact and intrinsic structural compliance for regulating physical interactions between mechanisms and environments. Howev

Leveraging a four-quadrant approach for evaluating Redpine Science

arXiv:2610.07937v1 Announce Type: new Abstract: Redpine Science gives models and agents a single access point to a wide range of peer-reviewed literature, queried directly through the Model Context Pr

Logbook: Extremely Long-form Audio Event Understanding

arXiv:2610.07338v1 Announce Type: cross Abstract: Audio benchmarks are built around short, pre-segmented clips, limiting model design to brief inputs or fixed vocabularies. To close this gap, we intro

LOGIC: An LLM Benchmark for Intent-Grounded Change Impact in Aerospace Electrical Systems

arXiv:2610.07580v1 Announce Type: new Abstract: Aerospace electrical-design revisions can contain multiple genuine changes, although an engineering request may authorize only a subset. Propagating eve

Lost in the bf16 Cast: Exporting Ternary Language Models Can Revert Most Low-Learning-Rate Code Changes

arXiv:2610.07853v1 Announce Type: cross Abstract: Ternary language models such as BitNet b1.58, Falcon-E and BitCPM are fine-tuned with higher-precision latent weights and deployed as ternary codes pr

M3SunAgent: Monocular 3D Spatial Understanding Agent for Metric Depth Estimation and 3D Visual Grounding

arXiv:2610.07982v1 Announce Type: new Abstract: Monocular metric depth estimation and 3D visual grounding represent the two complementary cornerstones of monocular 3D spatial understanding (M3Sun), fr

Machine Learning for German Redispatch Forecasting under Data Delays and Temporal Distribution Shift

arXiv:2610.08337v1 Announce Type: cross Abstract: Public redispatch records provide empirical data for grid congestion forecasting, but delayed reporting, zero-inflated distributions, and temporal shi

Machine learning Majorana topology using unsupervised and supervised learning

arXiv:2512.13825v2 Announce Type: replace-cross Abstract: In unsupervised learning, the training data for deep learning does not come with any labels, thus forcing the algorithm to discover hidden pat

MASC: A Multi-Agent Self-Calibration Framework with Latent Construct Alignment for Consistent Client Role-Playing in Psychological Counseling

arXiv:2610.08250v1 Announce Type: new Abstract: Large language models are increasingly used to simulate clients for counselor training and psychological counseling research, but reliable simulation re

MASKerade: Token-Routed Mask Experts for Dense-to-MoE Upcycling

arXiv:2610.07809v1 Announce Type: new Abstract: Sparsely activated Mixture-of-Experts (MoE) models increase model capacity without a proportional increase in per-token computation. Dense-to-MoE upcycl

Matching Object or Relation? Tracing Abstract Reasoning Inside VLMs

arXiv:2610.07646v1 Announce Type: new Abstract: Vision Language Models (VLMs) excel on visual benchmarks but fail systematically on tasks requiring abstract reasoning. Existing benchmarks document thi

Measuring climate backlash in Twitter and Reddit archives: Lexical definitions, recorded responses and participant turnover

arXiv:2610.07634v1 Announce Type: new Abstract: Social media archives are often used to study resistance to climate action, but words, response counters and observed participants do not measure the sa

MedHorizon: Towards Long-context Medical Video Understanding in the Wild

arXiv:2605.06537v2 Announce Type: replace Abstract: Medical multimodal large language models (MLLMs) have advanced image understanding and short-video analysis, but real clinical review often requires

Medical Image Alignment Assessment as a Test of Generalist Visual Reasoning in Frontier Multimodal Models

arXiv:2610.06896v1 Announce Type: new Abstract: Frontier multimodal large language models (MLLMs) are increasingly positioned as general purpose visual reasoners as part of the quest for artificial ge

MemFLoRA: Memory-Floor LoRA for CNN Adaptation at the Edge

arXiv:2610.08669v1 Announce Type: cross Abstract: On-device learning is necessary when the model encounters user-,sensor-, or environment-specific shifts after deployment. Although parameter-efficient

MemMux: Runtime Verification and Honest Resource Attribution for Fleets of Parallel Coding Agents

arXiv:2610.07257v1 Announce Type: new Abstract: Developers increasingly run a fleet of coding agents side by side on one workstation. The tools they reach for, terminal multiplexers like tmux and a ne

MINDSET: Energy-based Schema Evolution for Long Conversational Agent Memory

arXiv:2610.08586v1 Announce Type: new Abstract: Long conversational agents have become essential in our daily lives. They must remember what was said long back in order to help us efficiently complete

MiniScope: Authorizing Agents with Least-Privilege Permissions

arXiv:2512.11147v2 Announce Type: replace-cross Abstract: AI agents are increasingly granted autonomous access to sensitive user data and third-party services, making effective permission management a

Mission-Aware Attestation Envelopes for Time-Critical Autonomous Action: A Hardware-in-the-Loop V2I Study

arXiv:2610.08771v1 Announce Type: cross Abstract: An autonomous system that asks for a privileged physical action is usually gated on integrity evidence: a platform proves what it is running, and the

MoF: Preference-Aware Mixture Modeling for Black-Box LLM Personalization

arXiv:2610.08330v1 Announce Type: new Abstract: Proprietary Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks, yet aligning their outputs with diverse

Monte Carlo Estimation for KV Cache Eviction

arXiv:2610.07643v1 Announce Type: cross Abstract: Most KV-cache eviction methods ask, in effect, which memory appeared important while reading the prompt? We instead ask, which memory will matter whil

MoonGS: High-quality Representation of the Lunar Surface via Gaussian Splatting Using Robust Depth Features from Image Pairs

arXiv:2610.07110v1 Announce Type: new Abstract: High-quality 3D reconstruction of lunar terrain from sparse rover images is indispensable for autonomous lunar exploration, but remains challenging beca

Multi-Label Perceptual Bug Detection in Video Games using Deep Learning on Gameplay Footage

arXiv:2610.08593v1 Announce Type: new Abstract: Traditional approaches for automated bug detection in video games, such as manual testing, can be beneficial for the improvement of quality assurance, b

Multigroup Fairness and Omniprediction: Separations and Equivalences

arXiv:2610.07374v1 Announce Type: new Abstract: Omniprediction is a learning guarantee which requires a single predictor to be competitive relative to the best hypothesis from a benchmark class for an

Multimodal Knowledge Distillation for Gastric Adenocarcinoma Classification from Whole-Slide Images

arXiv:2610.07913v1 Announce Type: cross Abstract: Gastric adenocarcinoma (GA) is a leading cause of cancer-related mortality worldwide, and accurate histopathological subtype classification from whole

Natural Language Questions as an Interface for Knowledge Graphs: QRAKEN Graph Distillation and Semantic Self-Healing

arXiv:2610.08095v1 Announce Type: new Abstract: Natural-language access to RDF knowledge graphs is a core Semantic Web ambition. Large language models (LLMs) have advanced Text-to-SPARQL, yet on unfam

Navigation with RF Cues: Embodied Perception Action under Multipath Uncertainty

arXiv:2610.08105v1 Announce Type: new Abstract: Smart factory inspection requires robots to reach connected equipment without a prior map or known target coordinates. Radio frequency (RF) signals from

Near-Optimal Sample Complexity for Recursive Entropic Risk Reinforcement Learning with a Generative Model

arXiv:2610.06931v1 Announce Type: new Abstract: In this paper, we study the sample complexities of value and policy learning in finite discounted Markov decision processes (MDPs) under recursive entro