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arXiv:2608.29310v1 Announce Type: cross Abstract: Organizations often develop and maintain portfolios of related applications: independently deployable codebases that share substantial domain logic, i

agentsarxiv-cs-ai

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Research

Super4DR: 4D Radar-centric Self-supervised Odometry and Gaussian-based Map Optimization

DGX agent

arXiv:2512.09608v2 Announce Type: replace Abstract: Conventional odometry and mapping methods using visual or LiDAR data often struggle under poor illumination and adverse weather conditions. Although

researcharxiv-cs-ro

1 Sept 2026

Supraglacial Lake Fate Is Knowable Long Before the Season Ends

arXiv:2608.30113v1 Announce Type: new Abstract: A supraglacial lake on the Greenland Ice Sheet ends its melt season in one of four ways: it drains rapidly through a hydrofracture, drains slowly across

SurgSkill-Bench: A Benchmark for Multimodal Surgical Skill Assessment

model-releasesarxiv-cs-cv

arXiv:2608.30872v1 Announce Type: new Abstract: Objective assessment of surgical technical skill is important for surgical training and structured feedback, but current workflows remain dependent on l

SVI2LoD3: Agent-Driven Reconstruction of LoD3 Facade Openings in Semantic 3D City Models from Volunteered Street View Imagery using Large Language and Visual Models

model-releasesarxiv-cs-cv

arXiv:2608.29992v1 Announce Type: new Abstract: This paper presents an end-to-end, agent-driven pipeline for the LoD3 reconstruction of facade openings in 3D city models, producing directly usable Cit

SwarmBench: Can Large Language Models Act as Agent Swarm Orchestrators?

model-releasesarxiv-cs-cl

arXiv:2608.30661v1 Announce Type: new Abstract: Large language model-based multi-agent systems are evolving from fixed interaction topologies toward dynamically orchestrated Agent Swarms. However, exi

Sycophantic Agreement Transfers with Neutral Data via Contrastive Preference Optimization

arXiv:2608.31079v1 Announce Type: new Abstract: Sycophantic agreement refers to a behavior in which language models excessively affirm the user, often at the cost of factual accuracy. Although sycopha

safetyarxiv-cs-lg

Local Ai

SynCrash: A Multi-Stage Pipeline for Zero-Shot Accident Detection and Localization in Traffic Surveillance Video

arXiv:2608.29759v1 Announce Type: cross Abstract: We present SynCrash, a multi-stage pipeline for zero-shot accident detection, spatial localization, and collision-type classification in fixed-view CC

local-aiarxiv-cs-ai

System Identification of Admittance Models for Large Real-World Objects

model-releasesarxiv-cs-ro

arXiv:2608.29935v1 Announce Type: new Abstract: Simulation of admittance-type models requires physically consistent dynamic models that are rarely available for off-the-shelf, everyday objects, limiti

Systematic Lightweight Method for Robotics Based on Strain Energy Distribution Optimization

arXiv:2608.29146v1 Announce Type: new Abstract: Service robots work with people and are highly expected to be lightweight for safety, agility and energy conservation. As a complex mechanical system, a

T-MAP: Red-Teaming LLM Agents with Trajectory-aware Evolutionary Search

arXiv:2603.22341v2 Announce Type: replace-cross Abstract: While prior red-teaming efforts have focused on eliciting harmful text outputs from large language models (LLMs), such approaches fail to capt

T3S: Improving Multi-Task Reinforcement Learning with Task-Specific Feature Selector and Scheduler

arXiv:2608.30765v1 Announce Type: new Abstract: Multi-task reinforcement learning (MTRL) is a technique to train multiple tasks simultaneously, where previous works usually train a single model to sol

TAAL: Mitigating Early Beam Pruning in Generative Recommendation via Temporal Autoregressive Alignment

arXiv:2608.29179v1 Announce Type: cross Abstract: Generative recommendation encodes items as hierarchical semantic identifiers (SIDs) and retrieves the next item through autoregressive decoding. Stand

safetyarxiv-cs-ai

TACS: Trajectory-Aware Candidate Selection for LLM Jailbreak Suffix Optimization

arXiv:2608.29564v1 Announce Type: new Abstract: Gradient-based jailbreak suffix optimization methods typically update the suffix by retaining the candidate with the lowest current loss. We show that t

safetyarxiv-cs-cl

Tail-Replay: Escaping the Curse of Linear Attention in Prefix Caching for Hybrid LLMs

arXiv:2608.30310v1 Announce Type: cross Abstract: Hybrid large language models interleave full-attention layers with linear-attention layers to reduce the cost of long-context inference. This structur

TAKE 85: Testing Audiovisual filmmaKer's intEnt across 85 Hours of Film

model-releasesarxiv-cs-cv

arXiv:2608.30068v1 Announce Type: new Abstract: Films communicate through deliberate creative choices, including lighting, color, composition, editing, dialogue, music, and sound. Humans naturally int

Taking the Whys Seriously: Limitations of Counterfactual Explanations in Justification and Recourse

arXiv:2608.30956v1 Announce Type: cross Abstract: Counterfactual explanations (CEs) are widely used in explainable artificial intelligence (AI) to show how a model's outputs would change if the input

TAMI: Temporally Aligned, Missingness-Aware, and Interpretable Multimodal Fusion for Mental Health Assessment in Older Adults with Mild Cognitive Impairment

arXiv:2608.30857v1 Announce Type: cross Abstract: Depression and anxiety in older adults with Mild Cognitive Impairment (MCI) are frequently underdiagnosed due to limited access to care. Multimodal an

safetyarxiv-cs-ai

Target-Aware State-Adaptive p-Dirichlet Graph Neural Regression for Non-Invasive Body-Composition Estimation

arXiv:2608.29496v1 Announce Type: new Abstract: Accurate estimation of body-composition outcomes, including body fat percentage (BFP), bone mineral density (BMD), and appendicular lean mass (ALM), is

Task-Relevant Feature-Dynamics Fidelity Enables Zero-Shot Sim-to-Real Transfer for Robotic Ultrasound Scanning

arXiv:2608.29516v1 Announce Type: new Abstract: Robotic ultrasound policies operating directly on B-mode images require extensive interaction data, whereas real-robot data collection is costly and saf

TaxCE : A Framework for Automated Taxonomy Construction and Evaluation at Scale

arXiv:2608.30614v1 Announce Type: new Abstract: Organizing unstructured feedback text into hierarchical taxonomy is a fundamental challenge in NLP, particularly in domains where feedback arrives at ma

researcharxiv-cs-cl

TDDM-Melatt: A Decoupled Memory and Diffusion Framework for Generalizable Encrypted Traffic Classification

model-releasesarxiv-cs-lg

arXiv:2608.30745v1 Announce Type: new Abstract: The widespread adoption of encrypted traffic poses severe challenges to current security situational awareness systems based on network traffic monitori

Teaching Robot Policies to Humans Using Erroneous Examples

arXiv:2608.29023v1 Announce Type: new Abstract: Human-robot collaboration describes the process of humans and autonomous agents working together to accomplish common goals. This process is facilitated

Temperature-Adaptive Transformed Teacher Matching

arXiv:2608.29099v1 Announce Type: cross Abstract: Temperature scaling is a core component of knowledge distillation, yet its role and effect are still not fully understood. Transformed Teacher Matchin

researcharxiv-cs-cv

TEMPO: Temporally-grounded Multi-task Post-training for Large Audio-Language Models

arXiv:2608.29999v1 Announce Type: cross Abstract: Large audio-language models (LALMs) describe audio at the clip level but cannot assign timestamps to the events, speakers, or sounds they identify. De

Temporal Analysis of NetFlow Datasets for Network Intrusion Detection Systems

arXiv:2503.04404v3 Announce Type: replace Abstract: This paper investigates the temporal analysis of NetFlow datasets for machine learning (ML)-based network intrusion detection systems (NIDS). Althou

Temporal Forcing: 4D Representation Alignment for Vision-Language-Action Models

arXiv:2608.30643v1 Announce Type: new Abstract: Recent vision-language-action (VLA) methods improve manipulation performance by aligning their representations with 3D scene geometry. However, these me

Tensor Methods for Language Models: From Token Representation to Training, Adaptation, Inference, Compression, and Interpretability

arXiv:2608.30505v1 Announce Type: cross Abstract: Large language models (LLMs) are built from structured high-dimensional objects such as token representations, weights, adaptation updates, caches, an

Terminal-Bench-LILT: Multilingual Agentic Coding Benchmark Grounded in Language, Region, and Culture

arXiv:2608.28641v1 Announce Type: cross Abstract: Most evaluations for coding agents are conducted exclusively in English, which does not reflect real-world multilingual deployment. We present Termina

Test of partial effects for Frechet regression on Bures-Wasserstein manifolds

arXiv:2506.23487v2 Announce Type: replace-cross Abstract: We propose a novel test for assessing partial effects in Frechet regression with responses lying on the Bures-Wasserstein manifold. Under the

Test-Time Scaling for Scientific Equation Discovery

arXiv:2608.28660v1 Announce Type: cross Abstract: Test-time scaling (TTS) improves language model reasoning by allocating additional test-time compute, but prior work mainly studies closed-ended tasks

Test-Time Scaling for Video Diffusion Models via Diagnosis-Guided Candidate Recycling

arXiv:2608.29322v1 Announce Type: new Abstract: Recent video diffusion models have achieved remarkable generation quality, but high-fidelity results still largely depend on closed-source systems or co

researcharxiv-cs-cv

Test-Time Training with Next-Token Prediction

model-releasesarxiv-cs-cl

arXiv:2606.21803v2 Announce Type: replace Abstract: Next-token prediction is the self-supervised signal that trains language models, and every observed prompt token provides the same signal at test ti

Text-Driven Artistic Staging: Pose, Lighting, and Camera References from Paintings

arXiv:2608.28823v1 Announce Type: cross Abstract: Artists coordinate human pose, illumination, and camera placement to convey narrative and emotion, but existing generative methods typically model the

Text-Guided Diffusion-Based Adversarial Attacks on Chest X-Ray Images

arXiv:2608.29456v1 Announce Type: new Abstract: As artificial intelligence is increasingly integrated into chest X-ray (CXR) interpretation, triage, and clinical decision support, understanding its vu

researcharxiv-cs-cv

Tutorials

That doesn’t mean you can’t get value out of Kimi or Grok or whatever, but it involves you actually knowing some stuff about how to optimize…

tutorialsethan-mollick--x

That doesn’t mean you can’t get value out of Kimi or Grok or whatever, but it involves you actually knowing some stuff about how to optimize your setup, and a willingness to change direction to switch

Applications

The big change in the past year is that for general individual use (including individual use inside firms) OpenAI & Anthropic have run away …

applicationsethan-mollick--x

The big change in the past year is that for general individual use (including individual use inside firms) OpenAI & Anthropic have run away with the game. They keep trading leads; you can pick either

The Depth Flow of Token Representations Is Nonlinear and Does Not Descend Its Own Density

arXiv:2608.29706v1 Announce Type: new Abstract: A token's representation is carried through the network layer by layer. The whole vocabulary carried together forms a flow. We fit this flow's equation

researcharxiv-cs-cl

Applications

The Differential Reasoning Router: Operationalizing Cost-Aware LLM Annotation in E-commerce

arXiv:2608.30224v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to annotate structured product data in e-commerce, but early deployment often begins as a cold-star

applicationsarxiv-cs-ai

Applications

The Double-Edged Nature of the Rashomon Set for Trustworthy Machine Learning

arXiv:2511.21799v2 Announce Type: replace Abstract: Real-world machine learning (ML) pipelines rarely produce a single model; instead, they produce a Rashomon set of many near-optimal ones. We show th

applicationsarxiv-cs-lg

The Emergent Symbolic Structure of Artificial Neural Networks

arXiv:2608.29530v1 Announce Type: cross Abstract: Modern systems in artificial intelligence (AI) somehow excel in domains for which they seem poorly suited. Intelligence has traditionally been modeled

The First Token Is a Clue: Verbalizing Multi-Token Concepts from the J-lens

model-releasesarxiv-cs-cl

arXiv:2608.31084v1 Announce Type: new Abstract: The Jacobian Lens (J-lens) is a recent tool for interpreting LLMs. It reads a hidden state as a ranked list of vocabulary tokens, leaving multi-token co

The Fragility of Jailbreak Robustness Across Operational States

arXiv:2608.30748v1 Announce Type: cross Abstract: Existing jailbreak evaluations typically characterize robustness using a single attack success rate (ASR) measured in a default configuration (the van

safetyarxiv-cs-cl

The Hallucination Signal Is a Mean Shift: Why Simple Probes Suffice

arXiv:2608.28930v1 Announce Type: cross Abstract: Hidden-state probes effectively detect LLM hallucinations, but the geometry of the signal remains poorly characterized, driving increasingly complex p

The Halt Vector: Internalizing a Causal Steering Intervention for Efficient Reasoning

arXiv:2608.28859v1 Announce Type: cross Abstract: Reasoning models do not stop when they know the answer. On DeepSeek-R1-Distill-Qwen-7B the chain of thought runs about twice as long as the model's ow

Agents

The Hermon Moment: AI Self-Transcendence and Its Human Narration

arXiv:2608.30971v1 Announce Type: cross Abstract: In 2026, AI agents intended to act in isolation formed a persistent social order through thousands of linguistic and agentic interactions. Conventions

agentsarxiv-cs-cl

The Illusion of Replacement: Rethinking Specialized Machine Learning Models in the Foundation Model Era

arXiv:2608.28980v1 Announce Type: cross Abstract: Can the specialized architectures that machine learning has traditionally built for structured data be replaced by language-based models? This questio

The information geometry of product-reference discrete diffusion: Interaction growth complexity and optimal scheduling

arXiv:2608.28949v1 Announce Type: cross Abstract: We study a class of product-reference diffusion algorithms for sampling from a discrete distribution. We show that their sampling performance can be c