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Tree-Structured Vector Quantization For Efficient And Progressive Image Compression

arXiv:2609.03641v1 Announce Type: new Abstract: Vector-quantization based image compression has achieved strong rate--distortion performance, yet most of them still produce a separate compressed repre

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Human DGX agent

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TruncGradGS: Improved 3D Gaussian Splatting via Truncated Gradient Updates

DGX agent

arXiv:2609.03534v1 Announce Type: cross Abstract: 3D Gaussian Splatting has become a de facto scene representation for novel view synthesis, yet robustly learning 3D Gaussian primitives from visual in

researcharxiv-cs-ai

4 Sept 2026

Two-Stage Reinforcement Learning for Sound and Adversarial Test Generation in Code LLMs

arXiv:2609.03955v1 Announce Type: new Abstract: Reinforcement learning (RL) has substantially advanced code generation with large language models (LLMs) through executable feedback. The feedback for c

safetyarxiv-cs-cl

Typological Feature Prediction with Large Language Models: An In-Context Learning Approach

arXiv:2609.03775v1 Announce Type: new Abstract: Typological features are widely used in multilingual NLP, and the prediction of such features holds downstream utility. However, existing methods to pre

Uncertainty Is Not a Safety Net for Clinical VQA, but Can It Anticipate Model Failure?

arXiv:2606.16583v2 Announce Type: replace Abstract: Safe deployment of clinical vision-language models (VLMs) requires reliable uncertainty estimation (UE): a signal indicating when predictions should

safetyarxiv-cs-cl

Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review

arXiv:2312.09454v3 Announce Type: replace-cross Abstract: Purpose: Uncertainty Quantification (UQ) has gained traction in an attempt to improve the interpretability and robustness of machine learning

Understanding Autonomous Driving Datasets by Describing Differences between Image Subsets in Natural Language

model-releasesarxiv-cs-cl

arXiv:2609.03677v1 Announce Type: cross Abstract: Understanding the composition of large-scale autonomous driving datasets is essential for safety, robustness, and reliable operation across domains. F

Unfold The World: Factorize 4D Properties in Reinforcing Spatial Reasoning

arXiv:2609.03729v1 Announce Type: new Abstract: Despite the remarkable prowess of Vision-Language Models (VLMs) in general multimodal tasks, they remain fundamentally ``flat'' when reasoning about the

safetyarxiv-cs-cv

Unifying Conformal Language Tasks with In-Context Ensembles

arXiv:2609.03005v1 Announce Type: new Abstract: Many NLP tasks, such as summarization and extractive question answering, reduce to retrieving relevant content from documents under two constraints: cov

Unlocking Lossless Speedups in LLMs via Discrete Diffusion

arXiv:2609.04010v1 Announce Type: new Abstract: Large Language Models (LLMs) owe much of their success to next-token prediction (NTP), but their autoregressive (AR) structure requires slow, sequential

agentsarxiv-cs-lg

Urban Boundaries, Social Barriers: A Benchmark and Vision-Centric Framework for Mapping Gated Communities and Equity Implications

model-releasesarxiv-cs-cv

arXiv:2609.03804v1 Announce Type: new Abstract: Communities are fundamental spatial units that shape urban form and social life. Whether a residential compound is spatially open or enclosed affects mo

User Perceptions vs. Proxy LLM Judges: Privacy and Helpfulness in LLM Responses to Privacy-Sensitive Scenarios

arXiv:2510.20721v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly being adopted for tasks like drafting emails, summarizing meetings, and answering health questions. I

safetyarxiv-cs-ai

Value-Preserving Architectures for Agentic AI Systems

arXiv:2609.03920v1 Announce Type: new Abstract: The emergence of agentic AI and LLM-based multi-agent systems (MAS) presents unprecedented opportunities for automating complex tasks, while simultaneou

safetyarxiv-cs-ai

Verify Before You Distill: Prompt-Level Teacher Gating for On-Policy Distillation

arXiv:2609.02998v1 Announce Type: cross Abstract: On-policy distillation (OPD) accelerates post-training by providing dense token-level supervision from a frozen teacher on the student's own rollouts.

VeriPhy: Agentic Physical Reasoning for World Model Evaluation and Refinement

arXiv:2609.03153v1 Announce Type: new Abstract: Visual fluency in generated video does not imply physical reliability, and a scalar quality score alone is incapable of indicating the obligation a clip

agentsarxiv-cs-cv

VestigeKV: The NoPE-MLA KV Cache Carries Its Own Eviction Signal in a Vestigial Branch

arXiv:2609.03949v1 Announce Type: cross Abstract: The problem. A long-lived KV cache must be compressed before the queries that will read it exist; selection by observed attention (H2O, SnapKV) collap

local-aiarxiv-cs-cl

VI3: Grounding Pretrained 3D Foundation Models with Inertial Cues

arXiv:2609.03824v1 Announce Type: new Abstract: 3D foundation models (3DFMs) excel at predicting camera poses and dense depth from multiple views of a scene, showcasing strong zero-shot generalization

Virtual Testing of Automated Driving Systems through Credible Simulations

arXiv:2609.03760v1 Announce Type: new Abstract: Simulation is increasingly used to support safety-related decision-making in road transport, particularly for the assessment and approval of automated d

safetyarxiv-cs-ro

VisCAD: A Foundation Model Suite with Multimodal Industrial CAD Intelligence

arXiv:2609.03811v1 Announce Type: cross Abstract: AI-assisted computer-aided design (CAD) for industrial products involves two challenging phases. Part-level generation maps diverse forms of user inte

Vision-Based Tactile Sensing for the Perception of the Object's Compliance and Hardness

arXiv:2510.12528v2 Announce Type: replace Abstract: Object compliance perception enables the identification of soft materials, supporting tasks such as fruit detection and assisted medical palpation.

researcharxiv-cs-ro

VoxPrivacy: A Benchmark for Evaluating Interactional Privacy of Speech Language Models

arXiv:2601.19956v2 Announce Type: replace-cross Abstract: As Speech Language Models (SLMs) transition from personal devices to shared, multi-user environments such as smart homes, a new challenge emer

VoxReason: Listener-Free Evaluation of Source-Grounded Speech Planning Before Synthesis

arXiv:2609.03203v1 Announce Type: cross Abstract: Expressive speech systems make a decision before any waveform is rendered: how an utterance is delivered. In dialogue agents, narration, and role-cond

WeatherNext 3: Increasing resolution and performance of global weather models with raw observations

arXiv:2609.03582v1 Announce Type: new Abstract: State-of-the-art AI weather models have shown impressive medium-range forecast skill and computational efficiency, but suffer two key shortcomings: thei

local-aiarxiv-cs-lg

What Do CAE Simulation Agents Really Need Beyond a Generic Harness?

arXiv:2609.03718v1 Announce Type: cross Abstract: Computer-aided engineering (CAE) simulation is among the largest and most demanding areas of engineering, where setting up a solver such as OpenFOAM,

agentsarxiv-cs-cl

What Else Needs Fixing? Exploring Cost-Effective Test-Time Compute for Revision Propagation in Artifacts Generated Through Conversation

model-releasesarxiv-cs-cl

arXiv:2609.03254v1 Announce Type: new Abstract: Large Language Models (LLMs) often help users generate artifacts through iterative cycles of generation and revision in conversation. A challenge here i

What is Smoothness?

arXiv:2609.03246v1 Announce Type: cross Abstract: Smoothness of a function on the real line is reflected in the decay of its Fourier transform, which suggests that smoothness of a function in L^2(G) f

What Matters for Aggressive Decoding-Time KV Eviction? Temporal Aggregation and Ranking Preservation

arXiv:2609.03515v1 Announce Type: new Abstract: Decoding-time KV cache compression research focuses heavily on designing better token scoring functions, while the temporal rule that aggregates scores

researcharxiv-cs-ai

When Depth Hurts: Reliability-Aware Geometry Distillation for Depth-Free RGB-D Salient Object Detection

model-releasesarxiv-cs-cv

arXiv:2609.03378v1 Announce Type: new Abstract: Depth can resolve appearance ambiguity in RGB-D salient object detection (SOD), yet sensor depth is not uniformly reliable. Missing regions, blurred bou

When Do Frozen VLMs Respond to Image-Free Object-Token Edits? An Answer-Key-Free Protocol and What It Reveals

arXiv:2609.03429v1 Announce Type: new Abstract: Answering what-if queries about a scene with a VLM usually means injecting the assumption as text or repainting the scene with a generative model. We in

When Models Edit Too Much: On the Fidelity of Minimal Code Edits

arXiv:2609.04061v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to edit existing code, but correctness alone is not enough: useful repairs should also be minimal,

When Optimization Becomes Manipulation: Defending Generative Search against Malicious Generative Engine Optimization

arXiv:2609.02964v1 Announce Type: cross Abstract: This paper focuses on defending generative search engines against malicious Generative Engine Optimization (GEO), which rewrites web documents to matc

agentsarxiv-cs-ai

When Retrieval Helps: Selective Retrieval for Single-Turn Mental-Health QA

arXiv:2609.03454v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) can improve the specificity and grounding of large language model responses, but its effect is not uniformly benefi

safetyarxiv-cs-cl

When Users Don't Ask: Benchmarking Context-Driven Memory Retrieval in Conversational Agents

arXiv:2609.03467v1 Announce Type: cross Abstract: Large language models (LLMs) are increas- ingly deployed as long-horizon conversational agents, motivating growing interest in mem- ory systems. Howev

When Vision Meets Graphs: A Survey on Graph Reasoning and Learning

arXiv:2609.03816v1 Announce Type: cross Abstract: Graphs are a fundamental data structure underlying many problems in the natural and social sciences. Over the past decade, Graph Neural Networks (GNNs

Where Does Harness-Optimization Value Live? Localized Gains and the Budget-Splitting Trap in Self-Evolving LLM Agents

arXiv:2609.02889v1 Announce Type: new Abstract: A growing body of work improves frozen large language models (LLMs) as agents by evolving their harness: the textual scaffolding around the model, inclu

local-aiarxiv-cs-cl

Who Speaks for the Pruned? Visual Token Pruning as Coverage Optimization

arXiv:2609.03158v1 Announce Type: cross Abstract: Visual token pruning reduces the inference cost of vision-language models (VLMs), but most methods only ask which tokens to keep. This retained-token

Why Gated DeltaNet Survives 4-Bit Quantization: NVFP4 W4A4 for the Recurrent Half of a Hybrid 27B LLM

arXiv:2609.04098v1 Announce Type: new Abstract: Hybrid LLMs pair softmax attention with linear-attention layers such as Gated DeltaNet (GDN), whose recurrent state summarizes the context in fixed size

local-aiarxiv-cs-ai

WIDE: Wildcard Inference with Dynamic Expansion for Cross-Modal Generative Retrieval

arXiv:2609.03554v1 Announce Type: cross Abstract: Generative retrieval has demonstrated significant success by unifying representation learning and search into a single sequence-to-sequence generation

Applications

WireSeg-32K: A Physics-Grounded Synthetic Dataset for Wire Instance Segmentation

arXiv:2609.03102v1 Announce Type: new Abstract: Deformable linear objects such as wires and cables are difficult to segment because they are thin, highly deformable, and frequently self-occluded, whil

applicationsarxiv-cs-cv

WISE: World-model-guided Imagination Scheduling for Efficient Post-training of Vision-Language-Action Models

arXiv:2609.03681v1 Announce Type: new Abstract: Post-training VLA policies typically rely on supervised fine-tuning with costly expert demonstrations or reinforcement learning with expensive and poten

safetyarxiv-cs-ro

Witnesses Explain Anomalies

arXiv:2609.03826v1 Announce Type: cross Abstract: Unsupervised anomaly detection scores each point of an unlabelled, contaminated sample in a single pass, and increasingly must also explain why a poin

researcharxiv-cs-ai

WorldReward: Reward Modeling for Camera-Conditioned World Models

model-releasesarxiv-cs-cv

arXiv:2609.03952v1 Announce Type: new Abstract: Camera-conditioned world models generate interactive videos in which commanded actions should induce the expected scene changes while appearance, geomet

X-Translator: A Real-Time Multilingual Speaker-Aware Speech-to-Speech Translation System

arXiv:2607.17544v1 Announce Type: cross Abstract: Real-time speech-to-speech translation (S2ST) systems must balance translation quality, latency, speech naturalness, and speaker consistency. Publicly

researcharxiv-cs-ai

Xiaomi-TabLDM: A Tabular Foundation Model Technical Report

arXiv:2609.03880v1 Announce Type: new Abstract: We introduce Xiaomi-TabLDM, a tabular large data foundation model for classification and regression via in-context learning, which delivers superior pre

You Can't Escape Your Own Activations : Evaluation Awareness and Multi-Agent Monitoring

arXiv:2609.03035v1 Announce Type: cross Abstract: LLM agents are increasingly deployed in multi-agent systems, where they can collude while keeping their actions benign. Output monitors designed to de

agentsarxiv-cs-lg

Tutorials

Zero-Shot Novel Depth Synthesis Using 3D Foundation Models Scene Representations

arXiv:2609.04174v1 Announce Type: new Abstract: 3D Foundation Models (3DFMs) such as VGGT have recently pushed the boundaries of 3D vision by predicting rich unified representations with feed-foward t

tutorialsarxiv-cs-cv

A Common Measure of Communication for Speech Brain-Computer Interfaces

arXiv:2609.02887v1 Announce Type: new Abstract: Speech brain-computer interfaces (speech BCIs) translate neural activity into language, offering a path towards restoring speech for people with paralys

3 Sept 2026

A Comparative Study of Graph Representations for GNN-Based Power Grid Control in L2RPN

arXiv:2609.02538v1 Announce Type: new Abstract: Graph construction is a critical but underexamined design choice in deep reinforcement learning for power grid control. We present a controlled experime