Search: “models”

One LR Doesn't Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs

arXiv:2605.22297v1 Announce Type: new Abstract: Learning rate configuration is a fundamental aspect of modern deep learning. The prevailing practice of applying a uniform learning rate across all laye

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Protein Thoughts: Interpretable Reasoning with Tree of Thoughts and Embedding-Space Flow Matching for Protein-Protein Interaction Discovery

DGX agent

arXiv:2605.21522v1 Announce Type: cross Abstract: Protein-protein interactions (PPIs) govern nearly all cellular processes, yet computational methods for identifying binding partners typically produce

model-releasesarxiv-cs-lg

23 May 2026

Representation Gap: Explaining the Unreasonable Effectiveness of Neural Networks from a Geometric Perspective

arXiv:2605.21692v1 Announce Type: new Abstract: Characterizing precisely the asymptotic generalization error of neural networks using parameters that can be estimated efficiently is a crucial problem

Short-Term-to-Long-Term Memory Transfer for Knowledge Graphs under Partial Observability

arXiv:2605.22142v1 Announce Type: new Abstract: Reinforcement learning under partial observability requires deciding what information to retain, yet most memory-based approaches do not explicitly mode

The Neural Compiler: Program-to-Network Translation for Hybrid Scientific Machine Learning

arXiv:2605.22498v1 Announce Type: new Abstract: Scientific machine learning often requires combining known physics with unknown parameters or correction terms learned from data. Existing approaches ei

researcharxiv-cs-lg

Towards Explainability of SLMs by investigating Token Level Activation

arXiv:2605.22377v1 Announce Type: new Abstract: Transformer-based language models such as BERT having 110M+ parameters have revolutionized natural language understanding, yet their internal mechanisms

researcharxiv-cs-lg

When Are Teacher Tokens Reliable? Position-Weighted On-Policy Self-Distillation for Reasoning

arXiv:2605.21606v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a student on its own rollouts using a privileged teacher, but its standard objective weights all generated tok

3D LULC classification using multispectral LiDAR and deep learning: current and prospective schemes

arXiv:2605.22328v1 Announce Type: new Abstract: Land Use Land Cover (LULC) classification is essential for national 3D mapping, geospatial analysis, and sustainable planning. Multispectral (MS) LiDAR

A KL-regularization Framework for Learning to Plan with Adaptive Priors

arXiv:2510.04280v2 Announce Type: replace-cross Abstract: Effective exploration remains a central challenge in model-based reinforcement learning (MBRL), particularly in high-dimensional continuous co

safetyarxiv-cs-ro

A Task-Agnostic Algebraic Integrity Metric for Event-Camera Streams Toward SOTIF-Compliant Perception using Pearson Correlation Coefficient

arXiv:2605.21500v1 Announce Type: cross Abstract: Event cameras have emerged as a high-bandwidth, low-latency sensing modality for safety-critical perception in automated driving systems (ADS), offeri

Applications

AVI-HT: Adaptive Vision-IMU Fusion for 3D Hand Tracking

arXiv:2605.21714v1 Announce Type: new Abstract: We present AVI-HT, an adaptive visual-IMU fusion approach for tracking 3D hand poses by jointly modeling the egocentric image with on-glove 6-DoF IMU si

applicationsarxiv-cs-cv

ChronoMedKG: A Temporally-Grounded Biomedical Knowledge Graph and Benchmark for Clinical Reasoning

arXiv:2605.22734v1 Announce Type: new Abstract: Biomedical knowledge graphs (KGs) treat disease associations as static facts, but temporal information is crucial for clinical reasoning, e.g., a sympto

COCOTree: A Dataset and Benchmark for Open Tree-Structured Visual Decomposition

arXiv:2605.22068v1 Announce Type: new Abstract: We formalize and enable the task of open tree decomposition, which segments an image into hierarchical trees of visual components with unconstrained gra

Applications

Codec-Robust Attacks on Audio LLMs

arXiv:2605.20519v1 Announce Type: cross Abstract: Prior attacks on Audio Large Language Models (Audio LLMs) demonstrated that carefully crafted waveform-domain perturbations can force targeted adversa

applicationsarxiv-cs-ai

Cohesion-6K: An Arabic Dataset for Analyzing Social Cohesion and Conflict in Online Discourse

arXiv:2605.22447v1 Announce Type: new Abstract: The study of online discourse has become central to understanding societal polarization. While much research has focused on detecting overt toxicity, th

D3Seg: Dependency-Aware Diffusion for Brain Tumor Segmentation with Missing Modalities

arXiv:2605.22249v1 Announce Type: new Abstract: Accurate brain tumor segmentation using multiparametric MRI is critical for effective treatment planning. However, in clinical settings, complete acquis

Entropy-Guided Self-Supervised Learning for Medical Image Classification

arXiv:2605.21970v1 Announce Type: cross Abstract: Accurate and robust medical image classification is paramount for early disease diagnosis and treatment planning. However, challenges such as limited

FashionLens: Toward Versatile Fashion Image Retrieval via Task-Adaptive Learning

arXiv:2605.22552v1 Announce Type: new Abstract: Fashion image retrieval is a cornerstone of modern e-commerce systems. A unified framework that supports diverse query formats and search intentions is

Geometry-Adaptive Explainer for Faithful Dictionary-Based Interpretability under Distribution Shift

arXiv:2605.21849v1 Announce Type: cross Abstract: Mechanistic interpretability aims to explain a model's behavior by identifying causally responsible internal structures. Dictionary-based explainers s

researcharxiv-cs-cl

HyLoVQA: Dynamic Hypernetwork-Generated Low-Rank Adaptation for Continual Visual Question Answering

arXiv:2605.22035v1 Announce Type: cross Abstract: Continual Visual Question Answering (VQA) requires learning from non-stationary streams of visual inputs and questions while preserving past knowledge

InfVSR: Breaking Length Limits of Generic Video Super-Resolution

arXiv:2510.00948v2 Announce Type: replace Abstract: Real-world videos often extend over thousands of frames. Existing generative video super-resolution (VSR) approaches, however, face two persistent c

MLLMs Know When Before Speaking: Revealing and Recovering Temporal Grounding via Attention Cues

arXiv:2605.21954v1 Announce Type: new Abstract: Video temporal grounding (VTG), which localizes the start and end times of a queried event in an untrimmed video, is a key test of whether multimodal la

MM-Conv: A Multimodal Dataset and Benchmark for Context-Aware Grounding in 3D Dialogue

arXiv:2605.21796v1 Announce Type: cross Abstract: Grounding language in the physical world requires AI systems to interpret references that emerge dynamically during conversation. While current vision

MOTOR: A Multimodal Dataset for Two-Wheeler Rider Behavior Understanding

arXiv:2605.22550v1 Announce Type: new Abstract: Two-wheelers account for a disproportionately high share of road fatalities in the Global South. Research on two-wheeler rider behavior, however, lags f

NaviAgent: Graph-Driven Bilevel Planning for Scalable Tool Orchestration

arXiv:2506.19500v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) increasingly act as function-call agents that invoke external tools to tackle tasks beyond their static knowledge

safetyarxiv-cs-cl

Open-source LLMs administer maximum electric shocks in a Milgram-like obedience experiment

arXiv:2605.21401v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents that make sequences of decisions over extended interactions in high-stakes

safetyarxiv-cs-ai

PromptNCE: Pointwise Mutual Information Predictions Using Only LLMs and Contrastive Estimation Prompts

arXiv:2605.21776v1 Announce Type: new Abstract: Estimating mutual information from text usually requires training a task-specific critic, which limits its use in low-data settings. We ask whether larg

Applications

Quantizing Whisper-small: How design choices affect ASR performance

arXiv:2511.08093v2 Announce Type: replace-cross Abstract: Large speech recognition models like Whisper-small achieve high accuracy but are difficult to deploy on edge devices due to their high computa

applicationsarxiv-cs-cl

Local Ai

SegCompass: Exploring Interpretable Alignment with Sparse Autoencoders for Enhanced Reasoning Segmentation

arXiv:2605.22658v1 Announce Type: new Abstract: While large language models provide strong compositional reasoning, existing reasoning segmentation pipelines fail to transparently connect this reasoni

local-aiarxiv-cs-cv

SFN-YOLO: Towards Free-Range Poultry Detection via Scale-aware Fusion Networks

arXiv:2509.17086v2 Announce Type: replace Abstract: Detecting and localizing poultry is essential for advancing smart poultry farming. Despite the progress of detection-centric methods, challenges per

Agents

SpecHop: Continuous Speculation for Accelerating Multi-Hop Retrieval Agents

arXiv:2605.21965v1 Announce Type: new Abstract: Large language models increasingly use external tools such as web search and document retrieval to solve information-intensive tasks. However, multi-hop

agentsarxiv-cs-cl

ST-SimDiff: Balancing Spatiotemporal Similarity and Difference for Efficient Video Understanding with MLLMs

arXiv:2605.22158v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) face significant computational overhead when processing long videos due to the massive number of visual token

Steins;Gate Drive: Semantic Safety Arbitration over Structured Futures for Latency-Decoupled LLM Planning

model-releasesarxiv-cs-ro

arXiv:2605.22456v1 Announce Type: new Abstract: Cloud-hosted LLM driver agents provide useful semantic judgments, but their inference latency exceeds stepwise vehicle-control windows. Learned world mo

SURGE: An Event-Centric Social Media Sentiment Time Series Benchmark with Interaction Structure

model-releasesarxiv-cs-ai

arXiv:2605.21198v1 Announce Type: cross Abstract: Public events on social media generate large volumes of discussion whose collective dynamics carry direct value for opinion forecasting and crisis res

Training-Trajectory-Aware Token Selection

arXiv:2601.10348v2 Announce Type: replace Abstract: Efficient distillation is a key pathway for converting expensive reasoning capability into deployable efficiency, yet in the frontier regime where t

TransitLM: A Large-Scale Dataset and Benchmark for Map-Free Transit Route Generation

arXiv:2605.22355v1 Announce Type: new Abstract: Public transit route planning traditionally depends on structured map infrastructure and complex routing engines, and no existing dataset supports train

Two is better than one: A Collapse-free Multi-Reward RLIF Training Framework

arXiv:2605.22620v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has substantially improved the reasoning ability of LLMs, but often depends on external supervis

UniVL: Unified Vision-Language Embedding for Spatially Grounded Contextual Image Generation

arXiv:2605.21611v1 Announce Type: new Abstract: We introduce spatially grounded contextual image generation, a controllable image generation task that reframes the conditioning paradigm. Instead of su

APEX: Autonomous Policy Exploration for Self-Evolving LLM Agents

arXiv:2605.21240v1 Announce Type: new Abstract: LLM agents have shown strong performance across a wide range of complex tasks, including interactive environments that require long-horizon decision mak

APM: Evaluating Style Personalization in LLMs with Arbitrary Preference Mappings

arXiv:2605.21063v1 Announce Type: new Abstract: Typical LLM responses tend to follow a default style, even though users often have distinct preferences regarding tone, verbosity, and formality that th

Batched Single-Index Global Multi-Armed Bandits with Covariates

arXiv:2503.00565v3 Announce Type: replace-cross Abstract: The multi-armed bandits (MAB) framework is a widely used approach for sequential decision-making, where a decision-maker selects an arm in eac

Beyond Routing: Characterising Expert Tuning and Representation in Vision Mixture-of-Experts

arXiv:2605.20610v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models are often interpreted by analysing which categories are routed to which experts. However, routing alone does not reveal

Block-Sparse Global Attention for Efficient Multi-View Geometry Transformers

arXiv:2509.07120v2 Announce Type: replace Abstract: Efficient and accurate feed-forward multi-view reconstruction has long been an important task in computer vision. Recent transformer-based models li

Choose Wisely and Privately: Proactive Client Selection for Fair and Efficient Federated Learning

arXiv:2605.20975v1 Announce Type: new Abstract: Federated Learning enables collaborative model training across decentralized data sources without data transfer. Averaging-based FL is limited by the pr

safetyarxiv-cs-lg

ChunkFT: Byte-Streamed Optimization for Memory-Efficient Full Fine-Tuning

arXiv:2605.21177v1 Announce Type: cross Abstract: This work presents extsc{ChunkFT}, a memory-efficient fine-tuning framework that reformulates full-parameter fine-tuning around a dynamically activate

Agents

Code Generation by Differential Test Time Scaling

arXiv:2605.20473v1 Announce Type: cross Abstract: Test-time scaling has emerged as a promising approach for improving code generation by exploring large solution spaces at inference time. However, exi

agentsarxiv-cs-lg

Cross-lingual robustness of LLM-brain alignment and its computational roots

arXiv:2605.21049v1 Announce Type: new Abstract: Large language models (LLMs) reliably predict neural activity during language comprehension and transformer depth has been interpreted as mirroring hier

safetyarxiv-cs-cl

Cumulative Meta-Learning from Active Learning Queries for Robustness to Spurious Correlations

arXiv:2605.20771v1 Announce Type: new Abstract: Spurious correlations in real-world datasets cause machine learning models to rely on irrelevant patterns, undermining reliability, generalization, and

safetyarxiv-cs-lg