Search: “evaluation”

[Paper] WaveFront Decoding: Parallelized Self-Speculative Decoding for Looped Language Models

model-releasesr-localllama

Looped language models repeatedly apply a weight-shared block to increase effective depth without increasing parameter count, but the resulting T sequential recurrent-block calls per generated token s

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Research

PCLM: Small-target localization with frozen CLIP via prototype contrast and local magnification

DGX agent

arXiv:2610.05115v1 Announce Type: new Abstract: Small targets occupy few patches in a vision-language encoder, so spatial features often mix object appearance with surrounding content. We propose Prot

researcharxiv-cs-cv

6 Oct 2026

Physics is the Best Teacher: Consistency Learning for Time-Invariant Operators of Chaotic Dynamics

arXiv:2610.04108v1 Announce Type: new Abstract: Accelerating the prediction of long-term behavior in chaotic systems is crucial in scientific computing. However, existing methods rely on numerical sol

ProbeFlow: Training-Free Adaptive Flow Matching for Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2603.17850v2 Announce Type: replace Abstract: Recent Vision-Language-Action (VLA) models equipped with Flow Matching (FM) action heads achieve state-of-the-art performance in complex robot manip

Agents

Proxy Confidence: Auditing Black-Box LLM Agents with a Surrogate's Log-Probabilities

arXiv:2610.03894v1 Announce Type: cross Abstract: A deployed LLM agent emits tool calls, queries, and code that can be silently wrong -- by the time the error surfaces, the action has run. Frontier ch

agentsarxiv-cs-lg

PWM: Personalized World Models with Online Reinforcement Learning

arXiv:2610.04920v1 Announce Type: new Abstract: Pretrained world models can generate diverse environments, yet users often want to explore a particular scene specified by their own video. This require

safetyarxiv-cs-cv

PyINE: A Framework for Scalable Elicitation and Oversight via Code Execution

arXiv:2610.04737v1 Announce Type: cross Abstract: Reasoning models can remain capable of solving a task while still defaulting to cheaper but misleading shortcuts. This creates a central oversight pro

Radar2Plan: Benchmarking 4D Radar for End-to-End Open-Loop Ego-Trajectory Planning

model-releasesarxiv-cs-ro

arXiv:2610.06121v1 Announce Type: new Abstract: Adverse weather and poor illumination remain major challenges for robust ego-trajectory planning in mobile autonomy. 4D radar offers reliable sensing un

Readout Blindness: VLM Scores Miss the Spatial Direction Their Frozen Encoders Retain

arXiv:2610.06324v1 Announce Type: new Abstract: CLIP-like vision-language models remain a cornerstone of multimodal systems, yet their scores stay near chance on directed spatial relations, such as wh

researcharxiv-cs-cv

Reflection-Robust 6DoF Object Tracking with Light Fields

arXiv:2610.04883v1 Announce Type: new Abstract: Tracking the 6DoF pose of a moving rigid object is fundamental to robotics and autonomous driving, but existing trackers assume that object appearance i

RepICL: Reusable In-Context Prediction Across Heterogeneous Representation Spaces

arXiv:2610.05852v1 Announce Type: new Abstract: Frozen representations are widely reused for downstream classification, yet each new task typically requires fitting a new predictor. We ask whether the

Agents

Representational Control over Self-Report & Behavior Coherence in LLM Risk-Taking

arXiv:2610.04125v1 Announce Type: cross Abstract: Self-report is an appealing low-cost probe of an LLM's dispositions, but recent work finds only selective agreement between what models report and how

agentsarxiv-cs-lg

Resisting Adversarial Attacks in Deep Neural Networks using Diverse Decision Boundaries

arXiv:2208.08697v2 Announce Type: replace-cross Abstract: The security of deep learning (DL) systems is an extremely important field of study as they are being deployed in several applications due to

researcharxiv-cs-cv

ResOPD: Tail Residualization for Sparse On-Policy Distillation

arXiv:2610.04882v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student model on self-generated trajectories, but transmitting dense teacher distributions across long reasoning t

safetyarxiv-cs-lg

Tutorials

Robotic Long-Horizon Manipulation with Progressive In-Context Code Generation and Episodic Feedback

arXiv:2503.21969v4 Announce Type: replace Abstract: Robotic long-horizon manipulation requires robots to compose perception, reasoning, and action over extended task sequences, yet existing language-c

tutorialsarxiv-cs-ro

ROOT: Discovering Rewards for User-Specified Embodied Behaviors

arXiv:2610.04250v1 Announce Type: new Abstract: Reinforcement learning for embodied control remains constrained by the difficulty of reward specification. Although recent large language model (LLM)-ba

safetyarxiv-cs-ro

Tutorials

S^3N: A Spherical Spiral Scanning Network for Weather Forecasting

arXiv:2610.04338v1 Announce Type: new Abstract: Machine learning-based weather prediction (MLWP) has achieved strong performance in global weather forecasting. Recent Hierarchical Equal Area isoLatitu

tutorialsarxiv-cs-lg

SALUS: Automated Auditing of NL-to-SQL Benchmarks through Weak Supervision of Multi-Agent Output

arXiv:2610.05540v1 Announce Type: cross Abstract: Natural language to SQL (NL-to-SQL) benchmarks are foundational to progress in data analysis research, yet recent work has shown that widely-used benc

Saying, Not Knowing: Aggressively GGUF-Quantized Small Language Models Still Write Rare Words They Can No Longer Define

arXiv:2610.04403v1 Announce Type: cross Abstract: Post-training quantization to the GGUF format's mixed-precision K-quants is commonly how open-weight language models reach consumer hardware, yet its

Local Ai

Scalable Minimal-Change Learning for Controllable Image Editing

arXiv:2610.06021v1 Announce Type: new Abstract: Image editing should change only the attributes specified by an instruction while preserving everything else, yet current methods often make unintended

local-aiarxiv-cs-cv

Selective Backpropagation for Efficient Few-Shot Class-Incremental Learning

arXiv:2610.04003v1 Announce Type: cross Abstract: Few-Shot Class-Incremental Learning (FSCIL) requires models to continuously learn new classes from limited samples while retaining prior knowledge, un

SemCam: Semantic Camera Motion Control for Video Generation

arXiv:2610.05141v1 Announce Type: new Abstract: Controlling the camera relative to a moving subject in an existing video is challenging: behaviors such as maintaining a frontal view require the camera

SepRQ : Self-Supervised Speech Mixture Representation Learning via Mask-Free, Multi-Scale Source Separation

arXiv:2610.04690v1 Announce Type: cross Abstract: Self-supervised learning (SSL) is standard for speech representation learning, but mainstream models are designed around single-speaker audio, limitin

Sparse Calibration-Based Personalization of Kernel-Based Gait Phase and Speed Estimation Using Wearable IMUs

arXiv:2610.03931v1 Announce Type: new Abstract: This paper presents sparse calibration-based personalization for kernel-based gait phase and walking speed co-estimation from wearable inertial measurem

researcharxiv-cs-ro

Spectral Analysis of Molecular Features: When Richer Features Do Not Guarantee Better Generalization

arXiv:2510.14217v3 Announce Type: replace Abstract: The spectral properties of feature embeddings offer critical insights into model generalization and representation quality. While deep learning mode

Streaming Multi-Track Timeline Control for 3D Human Motion Generation

arXiv:2610.03873v1 Announce Type: new Abstract: Text-driven human motion generation has advanced substantially, yet most methods assume instructions are available before synthesis. Interactive applica

safetyarxiv-cs-cv

Applications

Synthetic-to-Real ViT-Based Pose Estimation of a Noncooperative UAV

arXiv:2610.04335v1 Announce Type: new Abstract: Remote pose estimation of noncooperative Unmanned Aerial Vehicles (UAVs) from imagery is critical, as they cannot be influenced or instrumented in advan

applicationsarxiv-cs-cv

The Score Is Not the Structure: Brain Alignment and Cross-Lingual Transfer

arXiv:2610.03827v1 Announce Type: cross Abstract: Researchers often support the claim that a model shares structure with the brain, or across languages, by reporting a similarity score. We ask what su

safetyarxiv-cs-lg

Tutorials

Training Numerical Intelligence via Auto-Diagnosis and Skill Discovery

arXiv:2610.03872v1 Announce Type: cross Abstract: AI agents are becoming increasingly capable of generating scientific code, but generating code is not the same as improving the algorithms behind it.

tutorialsarxiv-cs-lg

Transferable Adversarial Robustness for Speech Foundation Models via Hierarchical Stabilization

arXiv:2610.05310v1 Announce Type: cross Abstract: Frozen speech foundation models (SFMs) make downstream adaptation efficient: the backbone can stay fixed while a task learns layer fusion and a lightw

Two Americas of Well-Being: Divergent Rural-Urban Patterns of Life Satisfaction and Happiness from 2.6 B Social Media Posts

arXiv:2511.10542v2 Announce Type: replace-cross Abstract: Using 2.6 billion geolocated social-media posts (2014-2022) and a fine-tuned generative language model, we construct county-level indicators o

UltraDub: Towards Authentic Dubbing by Unifying Visually-Steered Flow Learning and Trajectory Guidance

arXiv:2610.05932v1 Announce Type: new Abstract: Visual voice cloning requires intelligible, speaker-consistent speech synchronized with visible articulation. However, sequential multimodal conditionin

WasserMan: Benchmark for Underwater Manipulation Policy Learning

model-releasesarxiv-cs-ro

arXiv:2610.04536v1 Announce Type: new Abstract: Underwater manipulation couples visual decisions, contact forces and a thruster-controlled floating base. We introduce WasserMan, to our knowledge the f

Watermarks and Fingerprints as Soft Bindings for Content Provenance: An Open-Licence Benchmark for Images, Audio and Video

arXiv:2610.04151v1 Announce Type: new Abstract: Content-provenance standards such as C2PA let a platform recover a stripped manifest through a soft binding: an invisible watermark read from the conten

What Do Verifiable Rewards Teach Video-Language Models About Time? A Controlled Multi-Model Study

arXiv:2610.03792v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has produced large reasoning gains in language models, and verifiable video benchmarks make it app

What Does an Observability Foundation Model Know?

arXiv:2610.05577v1 Announce Type: new Abstract: A linear probe can show that a label is recoverable from a model's hidden states, but not whether that goes beyond what the input already reveals, or wh

WILLIE: A Unified Framework and Benchmark for Wound Classification, Segmentation, and Localization

arXiv:2610.05341v1 Announce Type: new Abstract: Chronic wound management affects over 8.2 million patients in the United States and imposes substantial clinical and economic burden. Clinical wound ass

A generative-informed neuro-symbolic framework for syntactic ambiguity resolution: Evidence from Arabic DPs

arXiv:2610.02529v1 Announce Type: new Abstract: Syntactic ambiguity poses a persistent challenge for Arabic NLP, particularly in morphologically rich nominal constructions where multiple structu6ral i

Adaptive Mutual Distillation for Balanced Multi-Task Post-Training of Large Language Models

model-releasesarxiv-cs-cl

arXiv:2610.02856v1 Announce Type: new Abstract: Multi-task post-training of large language models (LLMs) aims to improve performance across tasks with unequal amounts of training data. Existing method

Adaptive Second-Order Solvers for Fast Stochastic Diffusion Sampling

arXiv:2610.03034v1 Announce Type: cross Abstract: Diffusion models rely on numerical solvers requiring time-discretization, which has a large influence on the tradeoff between sampling cost and qualit

ANCRe: Adaptive Neural Connection Reassignment for Efficient Depth Scaling

arXiv:2602.09009v2 Announce Type: replace-cross Abstract: Scaling network depth has been a central driver behind the success of modern foundation models, yet recent investigations suggest that deep la

researcharxiv-cs-ai

Answering clinicians' questions over trial evidence tables with verifiable, feedback-driven language models

arXiv:2610.02576v1 Announce Type: new Abstract: Systematic reviews condense clinical trials into evidence tables, yet clinicians can interrogate these tables only through database queries, and many qu

researcharxiv-cs-ai

Asterism: Exploring and Synthesizing Scattered Observations into Literature-Grounded Hypotheses and Theories

arXiv:2610.02673v1 Announce Type: cross Abstract: A theory draws many independent observations into one framework with novel hypotheses. A researcher building such a theory must synthesize observation

Author Representation Strategies for Zero-Shot Authorship Attribution: A Comparative Study of LLM-Based and Embedding-Based Approaches

arXiv:2610.03531v1 Announce Type: new Abstract: Authorship Attribution (AA) requires capturing fine-grained stylistic characteristics, making it particularly challenging in zero-shot (ZS) settings whe

Automating the Application of HCI Principles: Skills for On-Demand UI Construction, the Human-AI Space to Think, and the Future of HCI

model-releasesarxiv-cs-ai

arXiv:2610.02369v1 Announce Type: cross Abstract: Human-computer interaction (HCI) is in the middle of a transition: large language models can now generate functional user interfaces (UIs) on demand f

Beyond Reward Hacking: Proxy Divergence Across Four Layers of a Staged Humanoid Learning Pipeline

arXiv:2610.03196v1 Announce Type: new Abstract: A reinforcement-learning (RL) pipeline for a legged robot is assembled from proxies. A reward stands in for intended behaviour, a curriculum gate stands

safetyarxiv-cs-ro

Characterizing the Performance Gap in Human Activity Recognition for Older Adults

arXiv:2610.02711v1 Announce Type: cross Abstract: Human activity recognition (HAR) from wrist-worn accelerometers is increasingly used for health and behavioral tracking. Yet, most wearable HAR models

Contextual Flow Matching: Adaptive Step Selection in Flow Models for Efficient Visual Generation

arXiv:2610.03202v1 Announce Type: cross Abstract: Flow Matching enables high-quality visual generation via continuous-time dynamics, but inference remains costly due to multiple sequential function ev

researcharxiv-cs-ai