Search: “models”

Semi-Supervised Hyperbolic Hierarchical Clustering with Set-Level Structural Priors

arXiv:2606.01525v1 Announce Type: new Abstract: Semi-supervised hierarchical clustering aims to learn a tree structure consistent with data patterns and user-provided supervision. Supervision is usual

Tools

Serving MiniMax-M3 for efficient inference: Unlocking 1M-Token Context and Multimodality Without Regrets

DGX agent

MiniMax-M3 is a large language model capable of handling 1 million token contexts and multimodal inputs while maintaining efficient inference performance. Together AI's blog post discusses techniques

toolstogether-ai-blog

2 Jun 2026

SPADE-Bench: Evaluating Spontaneous Strategic Deception in Agents via Plan-Action Divergence

arXiv:2606.02380v1 Announce Type: cross Abstract: As LLM-based agents expand their operational scope, reliability becomes a prerequisite for real-world deployment. However, in practical applications,

Spatiotemporal Multi-Task Graph Transformer for Trip-Level Transit Prediction

arXiv:2606.00572v1 Announce Type: new Abstract: Passenger count data from public transit systems reveals urban mobility patterns and is essential for planning, operation, and optimisation. However, no

safetyarxiv-cs-lg

Speculative Sampling For Faster Molecular Dynamics

arXiv:2606.02455v1 Announce Type: new Abstract: Molecular dynamics (MD) is a key tool for simulating the dynamical behavior of atomic systems. However, MD is inherently serial, which makes it difficul

researcharxiv-cs-lg

Splatshot: 3D Face Avatar Generation from a Single Unconstrained Photo

arXiv:2606.01493v1 Announce Type: new Abstract: Reconstructing a photorealistic 3D face avatar from a single unconstrained photograph is challenging: feed-forward 3D Gaussian Splatting (3DGS) models d

Stabilizing Policy Optimization via Logits Convexity

arXiv:2603.00963v2 Announce Type: replace-cross Abstract: While reinforcement learning (RL) has been central to the recent success of large language models (LLMs), RL optimization is notoriously unsta

safetyarxiv-cs-cl

Stable Velocity: A Variance Perspective on Flow Matching

model-releasesarxiv-cs-cv

arXiv:2602.05435v2 Announce Type: replace Abstract: While flow matching is elegant, its reliance on single-sample conditional velocities leads to high-variance training targets that destabilize optimi

TAPS: Target-Aware Prefix Tree Selection for Diffusion-Drafted Speculative Decoding

arXiv:2606.00487v1 Announce Type: new Abstract: Using a diffusion model for parallel drafting is a promising approach for speculative decoding. By predicting tokens at multiple future positions in a s

Tempora: Characterising the Time-Contingent Utility of Online Test-Time Adaptation

arXiv:2602.06136v2 Announce Type: replace-cross Abstract: Test-time adaptation (TTA) offers a compelling remedy for machine learning (ML) models that degrade under domain shifts, improving generalisat

The Alignment Curse: Modality Alignment Supercharges Audio Attacks via Text Transfer

arXiv:2602.02557v2 Announce Type: replace-cross Abstract: Recent advances in end-to-end trained omni-models have substantially improved audio capabilities by strengthening text-audio modality alignmen

ThinkSwitch: Context Distillation with LoRA and Weight Interpolation for Specific-Purpose Reasoning Tasks

arXiv:2606.01080v1 Announce Type: cross Abstract: Large language models often improve on difficult tasks by spending inference-time compute on a reasoning trace before producing the final answer. That

Hardware

Threshold-Based Exclusive Batching for LLM Inference

arXiv:2606.00516v1 Announce Type: new Abstract: Mixed batching (MB)--interleaving prefill and decode in a single batch--has become the standard scheduling strategy for large language model (LLM) infer

hardwarearxiv-cs-ai

Tutorials

ToMAP: Training Opponent-Aware LLM Persuaders with Theory of Mind

arXiv:2505.22961v3 Announce Type: replace Abstract: Large language models (LLMs) have shown promising potential in persuasion, but existing works on training LLM persuaders are still preliminary. Nota

tutorialsarxiv-cs-cl

Agents

Towards a General Intelligence and Interface for Wearable Health Data

arXiv:2605.22759v2 Announce Type: replace Abstract: While ubiquitous wearable sensors capture a wealth of behavioral and physiological information, effectively transforming these signals into personal

agentsarxiv-cs-ai

Training-Free Composed Video Retrieval via Visual Representation-Guided Video-LLM Reasoning

arXiv:2606.02321v1 Announce Type: new Abstract: Recent advances in large vision-language models have expanded video retrieval from simple text-based search to more flexible scenarios, where users may

Understanding Identity Continuity in Thermal Video through Scene-Level Consistency

arXiv:2606.01694v1 Announce Type: cross Abstract: Thermal pedestrian MOT remains challenging because weak appearance cues and frequent detection interruptions cause severe trajectory fragmentation. We

UrbanFusion: Stochastic Multimodal Fusion for Contrastive Learning of Robust Spatial Representations

arXiv:2510.13774v2 Announce Type: replace-cross Abstract: Forecasting urban phenomena such as housing prices and public health indicators requires the effective integration of various geospatial data.

Agents

VideoBrain: Learning Adaptive Frame Sampling for Long Video Understanding

arXiv:2602.04094v2 Announce Type: replace Abstract: Long-form video understanding remains challenging for Vision-Language Models (VLMs) due to the inherent tension between computational constraints an

agentsarxiv-cs-cv

When Jokes Cross the Line: Analyzing Regular Humor and Dark Humor in YouTube Shorts

arXiv:2606.00046v1 Announce Type: cross Abstract: Video platforms such as YouTube have reshaped how users engage with entertainment and information, emphasizing brief, highly engaging content such as

Which Leakage Types Matter? A Quantitative Landscape Across 2,047 Benchmark Datasets

arXiv:2604.04199v2 Announce Type: replace Abstract: Twenty-eight within-subject counterfactual experiments across 2,047 iid tabular datasets, plus a boundary experiment on 129 temporal datasets, measu

Who Annotates in NLP? A Large-scale Assessment of Human Annotation Reporting between 2018 and 2025

arXiv:2606.02255v1 Announce Type: cross Abstract: Human annotation is the empirical foundation of much NLP research, from dataset construction to model evaluation, but papers often leave unclear who p

WildCat: Near-Linear Attention in Theory and Practice

arXiv:2602.10056v2 Announce Type: replace Abstract: We introduce WildCat, a high-accuracy, low-cost approach to compressing the attention mechanism in neural networks. While attention is a staple of m

X-Stream: Exploring MLLMs as Multiplexers for Multi-Stream Understanding

model-releasesarxiv-cs-cv

arXiv:2606.02482v1 Announce Type: new Abstract: While video streaming understanding has made significant strides, real-world applications, such as live sports broadcasting, autonomous driving, and mul

A hitchhiker's guide to Poisson gradient estimation

arXiv:2602.03896v2 Announce Type: replace-cross Abstract: Poisson-distributed latent variable models are widely used in computational neuroscience, but differentiating through discrete stochastic samp

safetyarxiv-cs-lg

A Novel Global Context-aware Deep Neural Network for Enhanced Brain Tumor Segmentation using Magnetic Resonance Images

arXiv:2605.30510v1 Announce Type: cross Abstract: Brain cancer's severity necessitates precise brain tumor segmentation, which is crucial for effective brain tumor diagnosis. Manual identification, bu

Aggregation Buffer: Revisiting DropEdge with a New Parameter Block

arXiv:2505.20840v2 Announce Type: replace Abstract: We revisit DropEdge, a data augmentation technique for GNNs which randomly removes edges to expose diverse graph structures during training. While b

AMNESIA: A Large Scale Medical Unlearning Benchmark Suite with Disease-Informed Analysis

model-releasesarxiv-cs-cl

arXiv:2605.30599v1 Announce Type: cross Abstract: Medical knowledge is continuously evolving. This creates a need to update or selectively forget information encoded in already-trained medical LLMs. M

An Odd Estimator for Shapley Values

arXiv:2602.01399v2 Announce Type: replace-cross Abstract: The Shapley value is a ubiquitous framework for attribution in machine learning, encompassing feature importance, data valuation, and causal i

Auto-Discovery-Bench: Diagnosing Structured State Tracking in Oracle-Guided Discovery

arXiv:2502.15224v2 Announce Type: replace-cross Abstract: Interactive discovery requires agents to maintain and update structured beliefs over many rounds of feedback. Before evaluating agents in nois

Automated Prediction of Postoperative Pancreatic Fistula Using Preoperative Computed Tomography

model-releasesarxiv-cs-cv

arXiv:2605.31539v1 Announce Type: new Abstract: Postoperative pancreatic fistula (POPF) is a serious complication after pancreatic resection, increasing morbidity, hospital stay, and healthcare costs.

Bayesian Inference with Shaped Deep Non-linear MLPs

arXiv:2605.30860v1 Announce Type: cross Abstract: A central aim of deep learning theory is to characterize how neural networks make predictions in the regime of simultaneously large model and training

researcharxiv-cs-lg

Beyond Agreement: Scoring Panel-Surfaced Biomedical Entity Candidates for Curator Triage

arXiv:2605.30826v1 Announce Type: cross Abstract: Biomedical NER is deceptively simple for modern LLMs: plausible biomedical mentions are easy to surface, but corpus-convention correctness depends on

Hardware

Beyond Test-Time Memory: State-Space Optimal Control for LLM Reasoning

arXiv:2603.09221v2 Announce Type: replace Abstract: Associative memory has long underpinned the design of sequential models. Beyond recall, humans reason by projecting future states and selecting goal

hardwarearxiv-cs-lg

Bounded Behavioral Indistinguishability for Black-Box LLM Distillation

model-releasesarxiv-cs-cl

arXiv:2605.30448v1 Announce Type: cross Abstract: Black-box LLM distillation is usually evaluated as an output-matching problem: a student is considered successful when its responses are semantically

ConTrans: Learning Text-enhanced Local-global Temporal Representations for Zero-shot Temporal Action Localization

arXiv:2605.30689v1 Announce Type: cross Abstract: Zero-shot Temporal Action Localization (ZS-TAL) aims to detect and locate previously unseen actions in untrimmed videos. However, existing approaches

De-attribute to Forget for LLM Unlearning

arXiv:2605.30919v1 Announce Type: cross Abstract: The rapid development of large language models (LLMs) has raised concerns on the use of inappropriate data for training, which has led to a growing in

Depth-Dependent Indirect Prompt Injection in Tool-Calling ReAct Agents: Injection Depth, Payload Framing, and Turn-Budget Sensitivity

arXiv:2605.30686v1 Announce Type: cross Abstract: ReAct agents that interleave chain-of-thought reasoning with tool calls are increasingly deployed for real tasks such as scheduling, file retrieval, a

DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation

arXiv:2506.11653v3 Announce Type: replace-cross Abstract: Dataset bias often leads deep learning models to exploit spurious correlations instead of task-relevant signals. We introduce the Standard Ant

Discovering Differences in Strategic Behavior Between Humans and LLMs

arXiv:2602.10324v2 Announce Type: replace Abstract: As Large Language Models (LLMs) are increasingly deployed in social and strategic scenarios, it becomes critical to understand where and why their b

Distilling LLM Feedback for Lean Theorem Proving

arXiv:2605.30861v1 Announce Type: new Abstract: Post-training for reasoning models typically combines supervised fine-tuning with reinforcement learning from verifiable rewards, most commonly with GRP

EchoRL: Reinforcement Learning via Rollout Echoing

arXiv:2605.31228v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards is an effective route for post-training to strengthen the reasoning capability of large language models

Effective Biological Representation Learning by Masking Gene Expression

arXiv:2605.31562v1 Announce Type: new Abstract: RNA sequencing produces rich and diverse datasets of gene expression, offering compelling insights into cellular state and function that have many appli

researcharxiv-cs-lg

EMBGuard: Constructing Hazard-Aware Guardrails for Safe Planning in Embodied Agents

model-releasesarxiv-cs-cl

arXiv:2605.30924v1 Announce Type: new Abstract: MLLM-powered embodied agents deployed in real-world environments encounter physical hazards. However, existing approaches lack explicit mechanisms for i

Expand Neurons, Not Parameters

arXiv:2510.04500v2 Announce Type: replace Abstract: This work demonstrates how increasing the number of neurons in a network without increasing its total number of non-zero parameters improves perform

Expert Merging in Sparse Mixture of Experts with Nash Bargaining

arXiv:2510.16138v2 Announce Type: replace Abstract: Existing expert merging strategies for Sparse Mixture of Experts (SMoE) typically rely on input-dependent or input-independent averaging of expert p

From Internal Diagnosis to External Auditing: A VLM-Driven Paradigm for Data-Free Online Backdoor Defense

arXiv:2601.19448v2 Announce Type: replace Abstract: Deep Neural Networks remain inherently vulnerable to backdoor attacks. Traditional test-time defenses largely operate under the paradigm of internal

safetyarxiv-cs-lg

From Leaky Thoughts to Private Reasoning: Controlling What LRMs Say to Themselves

arXiv:2602.24210v2 Announce Type: replace-cross Abstract: Large reasoning models (LRMs) produce reasoning traces (RTs) that often contain sensitive information. These leaky thoughts are difficult to c