Search: “benchmark”

Teach to Learn: Hint Annealing for Self-improving LLM Reasoning

arXiv:2609.34975v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) improves language-model reasoning by comparing verified rewards among multiple solution rollouts for each quer

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Teach Yourself Where to Look: On-Policy Attention Self-Distillation for Reasoning

DGX agent

arXiv:2609.33200v1 Announce Type: new Abstract: On-policy self-distillation trains reasoning models on their own trajectories using dense token distribution guidance from a privileged teacher with acc

safetyarxiv-cs-lg

29 Sept 2026

Temporal Modelling for Burn Scars on Sentinel-3

arXiv:2609.34596v1 Announce Type: new Abstract: Rapid and accurate burn scar delineation from satellite imagery is essential for post-fire damage assessment. Sentinel-3 OLCI, with daily revisit and 21

Applications

Test-Time Generalized Category Discovery

arXiv:2609.33937v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) and Generalized Category Discovery (GCD) are traditionally treated as disjoint problems: the former adapts models to domain s

applicationsarxiv-cs-cv

Text-Vision Synergistic Token Caching: A Training-Free Framework for Efficient Vision-Language-Action Inference

arXiv:2609.34319v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models enable generalizable robotic control but remain computationally expensive. Token caching provides a training-free, p

The GUI Is Not the State: Diagnosing State Aliasing in GUI World Models

arXiv:2609.32679v1 Announce Type: cross Abstract: GUI World Models (GUI-WMs) are increasingly used to predict future states for agent planning and simulation, yet most existing formulations condition

The Impact of Stochasticity on the Rashomon Effect in Machine Learning

arXiv:2609.32934v1 Announce Type: new Abstract: Neural network training is inherently stochastic, with factors such as weight initialization leading to distinct models despite comparable predictive pe

The Model Knows When to Stop: Training-Free Early Stopping for Long-Context Reading

arXiv:2609.34590v1 Announce Type: cross Abstract: Language models often process long inputs sequentially in chunks, but continuing to read after sufficient evidence has been acquired wastes computatio

safetyarxiv-cs-lg

The Selection Rule Decides the Winner: A Pre-Registered Audit of Open-Set Graph Anomaly Detection

arXiv:2609.33370v1 Announce Type: new Abstract: Open-set graph anomaly detection trains on a few labeled anomalies from one class and must also find anomaly classes that were never labeled. Published

Theory Guided and Interpretable Neural Operator Design for Partial Differential Equation Learning

arXiv:2609.33715v1 Announce Type: new Abstract: Accurate numerical solutions of partial differential equations (PDEs) are crucial in numerous science and engineering applications. In this work, we int

TIDE: Teacher-Student Transition via Informative Distillation and Exploration for Agentic RL

arXiv:2609.35058v1 Announce Type: new Abstract: Effective multi-turn agents require interaction strategies that coordinate information gathering, actions, and feedback over long horizons. GRPO is a re

safetyarxiv-cs-lg

Timeline-Bench: Evaluating Agents on Realistic Video-Editing Tasks, from Raw Footage to Final Cut

arXiv:2609.35143v1 Announce Type: new Abstract: AI agents increasingly carry out long-horizon professional work, but their evaluations rarely require a finished creative deliverable. To this end, we i

Token-Disentangled Latent Test-Time Scaling for Vision-Language Reasoning

arXiv:2609.35228v1 Announce Type: new Abstract: Latent test-time scaling improves reasoning by refining hidden states during inference, but existing methods typically apply a single scalar reward to a

Topology-Adaptive Hyperbolic Graph Attention Networks Guided by the Hyperbolic Sombor Index

arXiv:2609.32275v1 Announce Type: new Abstract: Hyperbolic geometry has emerged as a principled space for representing hierarchical graphs. However, existing hyperbolic graph neural networks typically

TopoMamba: A Load-Support Relation-Guided Multi-Directional State-Space Model for Topology Optimization

arXiv:2609.33688v1 Announce Type: cross Abstract: Deep learning has emerged as an efficient alternative for predicting high-performance material distributions in topology optimization. Existing method

Toward On-Chip Training of Spiking Neural Networks for Dense Event-Based Vision

arXiv:2609.32405v1 Announce Type: new Abstract: Event cameras provide low-latency, asynchronous visual sensing for resource-constrained robotics. Spiking neural networks (SNNs) process event streams n

Towards Eliminating Catastrophic Forgetting in the Curriculum Learning of Math Reasoning Tasks

arXiv:2609.33655v1 Announce Type: new Abstract: Curriculum learning has found broad application across numerous domains. Nevertheless, its effectiveness is intrinsically curtailed by catastrophic forg

Transform-Aligned Learned Features for Lossy Point Cloud Attribute Compression

arXiv:2609.34834v1 Announce Type: new Abstract: Transform-based methods provide an effective framework for point cloud attribute compression by representing attributes as transform coefficients. Intro

Local Ai

Trapped by Their Own Rollouts: Understanding Aggregation--Rollout Feedback in Federated On-Policy Distillation

arXiv:2609.32573v1 Announce Type: new Abstract: On-policy distillation (OPD) is a promising approach to language-model adaptation, aligning teacher supervision with the student's own generated traject

local-aiarxiv-cs-lg

TriDrive: Joint Driver, Vehicle, and Road Modeling for Forecasting and Driver Monitoring

arXiv:2609.33000v1 Announce Type: cross Abstract: Predicting how drivers, vehicles, and road scenes interact and evolve together is central to driver monitoring. Prior work models in-cabin activity or

TSGate: Timestep-Aware Gated Attention for Diffusion Transformers

arXiv:2609.34539v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have emerged as the dominant architecture for high-fidelity image and video generation. Recent DiT systems increasingly us

TTRSD: Test-Time Reinforcement Learning with Self-Distillation for Vision-Language Models

arXiv:2609.33414v1 Announce Type: new Abstract: Test-time reinforcement learning enables vision-language models (VLMs) to adapt using unlabeled inputs. However, repeated sampling under fixed visual co

TwinS-GCN: Spectral conjugate for Spectral Graph Convolutional Networks

arXiv:2609.32940v1 Announce Type: new Abstract: Graph convolutional networks propagate information by repeated local aggregation through a graph shift operator; i.e., a K-layer network reaches K hops

UMR: Universal Manipulation Representation

model-releasesarxiv-cs-ro

arXiv:2609.34256v1 Announce Type: new Abstract: General-purpose embodied manipulation hinges on a unified action representation that generalizes across embodiments and scales readily. Yet existing pol

Uncovering Ordinal-Matching Bias in Audio-Visual LLMs

arXiv:2609.34223v1 Announce Type: new Abstract: This work aims to improve how audio-visual large language models (AVLLMs) associate speech with the correct visible speaker in multi-speaker scenes. We

UniBYD: A Unified Framework for Learning Robotic Manipulation Across Embodiments Beyond Imitation of Human Demonstrations

model-releasesarxiv-cs-ro

arXiv:2512.11609v3 Announce Type: replace Abstract: In embodied intelligence, the embodiment gap between robotic and human hands brings significant challenges for learning from human demonstrations. A

Tutorials

Unlocking Few-Step Diffusion for Faithful Previews

arXiv:2609.34406v1 Announce Type: cross Abstract: Sampling latency compounds in diffusion workflows, where users generate and discard many candidates before keeping one. Surprisingly, the poor outputs

tutorialsarxiv-cs-cv

UNMATCH: Selective Unbalanced Token-Patch Matching for Forensic Image-Claim Verification

arXiv:2609.31766v1 Announce Type: new Abstract: Contextual image misuse pairs an image with a misleading claim. We study image-claim correspondence in fact-checked pairs containing out-of-context reus

Unveiling Implicit Advantage Symmetry: Why GRPO Struggles with Exploration and Difficulty Adaptation

arXiv:2602.05548v4 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR), particularly GRPO, has become the standard for eliciting LLM reasoning. However, its efficien

Agents

V-Gym: Enhancing Agentic Visual Reasoning via Skill-Data Co-Evolution

arXiv:2609.34682v1 Announce Type: new Abstract: Advances in multimodal understanding, reasoning, and tool use enable agents to tackle increasingly complex visual reasoning tasks. By distilling past ex

agentsarxiv-cs-cv

Verifiable Visual Rewards Transfer from Synthetic Scenes to Natural Prompts

arXiv:2609.35641v1 Announce Type: cross Abstract: Precise instruction following in image generation, such as satisfying object counts and spatial relations, remains an open challenge at least in part

researcharxiv-cs-cv

Applications

ViCoR: Reliable Molecular Structure Extraction via Spatially Aligned Verification and Executable Revision

arXiv:2609.33603v1 Announce Type: new Abstract: Reliable optical chemical structure recognition (OCSR) is essential for building high-quality chemical data from scientific literature, yet even small r

applicationsarxiv-cs-cv

VideoPhysEdit: Physical Counterfactual Video Editing via Rigid-Body Physical Scene Reconstruction

arXiv:2609.35134v1 Announce Type: new Abstract: Video editing has advanced substantially in recent years, with methods increasingly accounting for the visual consequences of edits, such as changes to

What Can a Leaderboard Certify? Compositional Controllability for Fair Evaluation and Training of Biomedical Literature-Review Agents

arXiv:2609.32318v1 Announce Type: new Abstract: Leaderboards rank long-horizon agents by their final outputs. Yet a higher score alone does not establish whether two systems are comparable or which st

Tutorials

What Should a Streaming Video Model Remember?

arXiv:2606.16353v2 Announce Type: replace Abstract: Streaming video understanding models must answer queries at any moment during an ongoing stream, using only what they have observed so far and under

tutorialsarxiv-cs-cv

What Should Federated LoRA Share? FedSAIL via Input-aware Subspace Alignment

arXiv:2609.32485v1 Announce Type: new Abstract: Federated low-rank adaptation (LoRA) requires identifying an update structure that is shared across heterogeneous clients. Prior work reports strong sim

When Noise Meets Long-Tail: Feature-Threshold Dual Calibration for Robust Pseudo-Labeling

arXiv:2609.33668v1 Announce Type: new Abstract: Pseudo-labeling has become a cornerstone of learning from unlabeled data in semantic segmentation. Yet its effectiveness drops sharply in real-world sce

When Should Humans Step In? Optimal Human Dispatching in AI-Assisted Decisions

arXiv:2603.13688v2 Announce Type: replace-cross Abstract: AI systems increasingly assist decision making by producing cheap factor-level assessments of complex inputs, but these assessments can be bia

Applications

When Should the Count Change? Learning State Maintenance for Causal Video Counting

arXiv:2609.35416v1 Announce Type: new Abstract: Continuous video counting requires distinguishing new observations from new objects or completed events. We introduce StaMina (State Maintenance), which

applicationsarxiv-cs-cv

When Text Matters: Design Principles for Visual Token Pruning in Vision-Language Model

arXiv:2609.34861v1 Announce Type: new Abstract: Visual token pruning has been widely studied as a practical approach to reducing the computational cost of large vision-language models. However, it str

researcharxiv-cs-cv

When VLMs Trust Context: Evaluating Scene Text Recognition under Misleading Context

arXiv:2609.34781v1 Announce Type: new Abstract: Vision-language models (VLMs) can read text in natural scenes, but their predictions may be influenced by the surrounding context. When the printed text

Where Memory Belongs: Ledger, an Object Ledger for Memory-Augmented VLAs

arXiv:2609.34554v1 Announce Type: new Abstract: Memory is essential for long-horizon, partially observed robotic manipulation: a robot must remember which object was placed in a drawer, whose cup it m

safetyarxiv-cs-ro

WhiteCon: Semi-Supervised Domain Adaptation Regression Through Whitening Transform and Dual Consistency

arXiv:2609.34078v1 Announce Type: new Abstract: Domain adaptation is crucial for addressing distributional shifts that degrade model performance across domains. While most existing research has center

Who Is Left of Whom? Tracing Spatial Evidence and Role Binding in Relative-Position Reasoning

arXiv:2609.35486v1 Announce Type: cross Abstract: High instance-level accuracy can mask inconsistencies in spatial reasoning when objects exchange positions or their roles are reversed in the query. T

researcharxiv-cs-cv

WorldGraph: Graph-Native World Modeling

arXiv:2609.34159v1 Announce Type: cross Abstract: World models infer latent states of an environment to capture its underlying dynamics and predict future evolution. Many real-world environments, howe

Write Back the Delta: Revisiting the Same Tokens with Fresh Representations

arXiv:2609.32457v1 Announce Type: new Abstract: Transformers process information strictly forward through depth, preventing deeper computation from revisiting and refining earlier representations. To

YuE2: Unifying Symbolic and Audio Music Generation at Frontier Quality

arXiv:2609.33757v1 Announce Type: cross Abstract: Symbolic models make melody, harmony, rhythm, and form explicit but typically stop before a finished recording; audio models produce complete songs wh

A Survey on Fake Review Detection: From Pre-trained Language Models to Large Language Models