Search: “model-releases”

ActionLens: Diagnosing Spatial-Temporal Binding Failures in Vision-Language Models

arXiv:2609.34547v1 Announce Type: new Abstract: Video-capable vision-language models score above 80% on popular benchmarks yet struggle with spatial-temporal binding: associating the right action with

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Model Releases

Active Causal Discovery Benchmark: Evaluating LLM Agents Under Budgeted Interventions

DGX agent

arXiv:2609.31675v1 Announce Type: new Abstract: We introduce the Active Causal Discovery Benchmark (ACDB), an SCM-grounded environment for evaluating whether LLM agents recover causal graph structure

model-releasesarxiv-cs-lg

29 Sept 2026

Active Feature Acquisition With Incomplete Training Data

arXiv:2609.32325v1 Announce Type: new Abstract: In many prediction tasks, acquiring all features can be a prohibitively expensive or outright impossible task. Further, in many cases a static subset of

AD-E2E-JEPA: A Joint-Embedding Predictive Architecture For End-to-End Autonomous Driving

arXiv:2609.34085v1 Announce Type: cross Abstract: Autonomous driving requires extit{world models} that can understand the physical world, reason and plan, and operate safely. In this paper, we first s

Adapting Vision-Language Models for Human-Readable XAI in Industrial Object Detection

arXiv:2609.31690v1 Announce Type: new Abstract: Explainable Artificial Intelligence (XAI) solutions are essential for building trust in AI technologies and their integration in real manufacturing line

Adaptive Ensemble Selection for Noisy Labels on Tabular Data

arXiv:2609.32976v1 Announce Type: new Abstract: Incorrect or corrupted labels in tabular datasets can significantly degrade supervised learning performance, particularly when mislabeling is subtle and

Advanced Policies: A First-Principles Path from Policy Gradient to Q-Learning

arXiv:2005.08844v3 Announce Type: replace Abstract: We apply entropy to reinforcement learning in two ways: entropy-augmented reward defines the soft objective, while relative-entropy regularization c

Adversarial Consistency-Guided Representation Learning for Multi-view Clustering

arXiv:2609.35212v1 Announce Type: new Abstract: Multi-view clustering aims to capture cross-view consistency while exploiting view-specific information. However, shared representations learned to capt

AevaScenes: An FMCW LiDAR Dataset and Benchmark for Long-Range Perception

arXiv:2609.33230v1 Announce Type: new Abstract: FMCW LiDAR measures per-point radial Doppler velocity alongside range, providing a motion cue unavailable in conventional time-of-flight sensors. Exploi

AgentPerfBench: A Benchmarking and Evaluation Suite for Inference Performance of Agentic LLMs

arXiv:2609.34683v1 Announce Type: new Abstract: The optimization of LLM serving engines, such as vLLM and SGLang, is largely benchmark-driven: optimizations, scheduling policies, hardware and system d

Agnostic Smoothed Online Regression with Adversarial Responses

arXiv:2609.32478v1 Announce Type: cross Abstract: We study smoothed online prediction with bounded adversarial responses. This widely studied framework bridges i.i.d. sampling and adversarial covariat

AIM-ZO: Activation-Informed Subspace Maintenance for Zeroth-Order LLM Fine-Tuning

arXiv:2609.35257v1 Announce Type: new Abstract: Zeroth-order (ZO) optimization offers a memory-efficient alternative for LLM fine-tuning by estimating updates only from forward evaluations of perturbe

ALDER: Discovering the Laws of a World by Acting in It

arXiv:2609.33728v1 Announce Type: new Abstract: Reliable world models should not only predict future states but express how actions change the world in an explicit, transparent and testable form, such

ALICE: In-context, Zero-shot, Mutual Information Estimation

arXiv:2609.34962v1 Announce Type: new Abstract: Estimating mutual information (MI) from samples is a central objective in a variety of scientific fields. Modern neural estimators are accurate in the l

Alignment-Guided Flow Transformer for Efficient Vision-Language-Action Policy Learning

arXiv:2609.34467v1 Announce Type: new Abstract: Recent advances in Vision-Language-Action (VLA) models point toward general-purpose robotic intelligence by unifying perception, instruction, and contro

Allspark: Weak to Strong Transfer via Alternating Chain of Thought

arXiv:2609.32913v1 Announce Type: new Abstract: Recent progress in frontier models has renewed interest in large-scale reinforcement learning (RL), but the cost of generating large-model rollouts make

AmbiModBench: Benchmarking Gene Perturbation Prediction Beyond Shared Responses

arXiv:2609.32527v1 Announce Type: cross Abstract: Predicting cellular responses to genetic perturbations helps prioritize experiments in single-cell genomics, where exhaustive measurement is infeasibl

Amnesia by Design, Memory By Necessity: Persistent State for Document Intelligence

arXiv:2609.32041v1 Announce Type: new Abstract: Modern Document AI reads contracts, extracts fields, reasons over tables, and grounds answers to page regions, then forgets everything. Processing an am

Analytic-Walk Rotary Positional Encodings for Graphs

arXiv:2609.32178v1 Announce Type: new Abstract: Rotary position encodings make attention sensitive to relative position, but extending them to graphs requires choosing how graph structure enters the r

AnchorRep: Defending LLMs Against Cross-Model Adversarial Transfer via Representation Repulsion

arXiv:2609.32602v1 Announce Type: new Abstract: Adversarial attacks optimized on a single open-weight LLM can transfer to and jailbreak architecturally different models, allowing an attacker with whit

Annealed Sinkhorn with Momentum: Certified Unregularized Optimal Transport in Linear Memory

arXiv:2609.33814v1 Announce Type: cross Abstract: We characterize Bregman Douglas-Rachford splitting (BDRS) for unregularized discrete optimal transport and develop an anytime primal-dual certificate

Anytime-Valid LLM Leaderboards via Benchmark-weighted and Block-Factorized e-Processes

arXiv:2609.32248v1 Announce Type: new Abstract: Large language model (LLM) leaderboards compare model capabilities by ranking models according to their mean performance on fixed benchmarks. However, v

Apparent Compression, Real Stability: The Intrinsic Dimension of Learning a Quantum Wavefunction

arXiv:2609.33193v1 Announce Type: new Abstract: How many directions in weight space does training need? The intrinsic dimension answers this with the smallest number of random directions in which trai

AquaWAM: A Dynamics-aware World Action Model for Underwater Embodied Agents

model-releasesarxiv-cs-ro

arXiv:2609.33299v1 Announce Type: new Abstract: World Action Models (WAMs) are becoming increasingly important and useful for embodied intelligence, as they enable robots to anticipate the consequence

ARCH-B: Architectural Representation, Comprehension and Hierarchy Benchmark

arXiv:2609.34047v1 Announce Type: new Abstract: Multimodal models increasingly interpret visual environments, but their ability to recognize the same building across photographs, floor plans, elevatio

Are We Making Progress in Multimodal Domain Generalization? A Comprehensive Benchmark Study

arXiv:2605.06643v2 Announce Type: replace Abstract: Despite the growing popularity of Multimodal Domain Generalization (MMDG) for enhancing model robustness, it remains unclear whether reported perfor

ARS: Agentic Reward System for Robot Learning

arXiv:2609.34484v1 Announce Type: cross Abstract: Progress reward modeling is the problem of estimating how a robot's behavior changes task progress over time. Reliable estimation requires distinguish

ArticulateArena: A Metric for Articulated Kinematics

arXiv:2609.33931v1 Announce Type: cross Abstract: Modern methods reconstruct or generate simulation-ready articulated objects, predicting not only their geometry but also how their parts are connected

AttentionViG: Cross-Attention-Based Dynamic Neighbor Aggregation in Vision GNNs

arXiv:2509.25570v2 Announce Type: replace Abstract: Vision Graph Neural Networks (ViGs) have demonstrated promising performance in image recognition tasks against Convolutional Neural Networks (CNNs)

Attribution Gaps in Zero-Training LLM+OVOD Pipelines: A Fine-Grained Analysis of the CAAP--SNAP Discrepancy

arXiv:2609.32567v1 Announce Type: new Abstract: LAOD and similar zero-training LLM+open-vocabulary-detector (OVOD) pipelines score two things separately: class-agnostic localization accuracy (CAAP) an

Audio-JEPA: Joint-Embedding Predictive Architecture for Audio Representation Learning

arXiv:2507.02915v2 Announce Type: replace-cross Abstract: Building on the Joint-Embedding Predictive Architecture (JEPA) paradigm, a recent self-supervised learning framework that predicts latent repr

Augmented Feature Boosting for Multicalibration

arXiv:2609.33891v1 Announce Type: new Abstract: Multicalibration requires a predictor's residuals to be unbiased not only globally, but also after conditioning on the predictor's own level sets and re

AutoExpert: Automating 3D LiDAR Annotation from Expert-Crafted Guidelines

arXiv:2506.02914v3 Announce Type: replace Abstract: The contemporary paradigm of scaling data annotation, crucial for developing machine learning solutions, is to hire ordinary human annotators and in

AutoHGNN: Robust and Efficient Neural Architecture Search for Hypergraph Neural Networks

arXiv:2609.33392v1 Announce Type: new Abstract: Hypergraph neural networks have achieved significant success in recent years. However, manual architecture crafting is labor-intensive and often fails t

Automated Species Identification in Camera Trap Images for Wildlife Conservation

arXiv:2609.35420v1 Announce Type: new Abstract: Wildlife conservation involves protecting, preserving, and managing wildlife species and their habitats. With today's rapid pace of human development, c

Autonomous phase discovery

arXiv:2609.33802v1 Announce Type: cross Abstract: Understanding quantum phases of matter has long relied on physicists' intuition and mathematical tools such as symmetry and topology. Remarkably succe

Autonomous Research Project Management as an Agent Skill: A Case Study in Exact Spectral Spatial Regression

arXiv:2609.31683v1 Announce Type: new Abstract: This work presents an end-to-end demonstration of autonomous machine learning research conducted by an agent skill on consumer hardware. The demonstrati

AutoRef: Harness Optimization for Agentic Multi-Reference Image Generation

arXiv:2609.35530v1 Announce Type: new Abstract: Recent image generation models can take multiple reference images as input and combine them into a new image. However, multi-reference image generation

Averaged Mirror Descent and Dual Gradient Methods: Convergent Algorithms for Entropic Gromov-Wasserstein Problem

arXiv:2609.31848v1 Announce Type: new Abstract: The Gromov-Wasserstein (GW) distance measures the discrepancy between metric measure (mm) spaces and identifies optimal alignments between them based so

BA-DPO: Bias-Adjusted Direct Preference Optimization for Language Model Alignment

arXiv:2609.35044v1 Announce Type: new Abstract: Preference-based alignment methods such as Direct Preference Optimization (DPO) use pairwise preferences labeled by human annotators to fine-tune langua

Background Gradients Shape Memorization in Flow Matching

arXiv:2609.33210v1 Announce Type: new Abstract: Repetition is closely associated with memorization in generative models, but how other training images affect the retention and copying of targets remai

BALAR : A Bayesian Agentic Loop for Active Reasoning

arXiv:2605.05386v2 Announce Type: replace-cross Abstract: Large language models increasingly operate in interactive settings where solving a task requires multiple rounds of information exchange with

Before Answering: Evidence Sufficiency under Size-Matched Memory Construction

arXiv:2609.32269v1 Announce Type: cross Abstract: Agents that answer questions from compressed or retrieved memory must recognize when the evidence a query needs is no longer in memory. Benchmarks for

Behavioral Foundation Models for Quality Diversity

arXiv:2609.35615v1 Announce Type: new Abstract: Behavioral Foundation Models (BFMs) are an emerging paradigm in reinforcement learning, playing a role analogous to large language models in natural lan

Benchmarking EEG Foundation Models at Scale: Lessons from 20,000 Evaluations

arXiv:2609.32743v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models (FMs) promise transferable neural representations, yet their advantages over strong supervised baselines

BERT4DTI : BERT-based Model for Predicting Drug-Protein Interactions

arXiv:2609.33254v1 Announce Type: new Abstract: Understanding how drugs interact with protein targets is fundamental to drug discovery, drug repurposing and the early identification of promising thera

Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection

arXiv:2609.34143v1 Announce Type: new Abstract: Existing 3D industrial anomaly detection mainly targets local geometric deviations. In contrast, many industrial anomalies violate object-level design o

Beyond Gradient Flow: Identifiability and Recovery from Distribution Snapshots

arXiv:2609.35060v1 Announce Type: new Abstract: Inferring dynamics from snapshots of evolving distributions is fundamentally underdetermined: the Fokker-Planck equation constrains the drift F only thr