arXiv AI
Jun 6
Towards One-to-Many Temporal Grounding
arXiv:2606. 06294v1 Announce Type: cross Abstract: Temporal Grounding (TG) aims to localize video segments corresponding to a textual query.
Benchmarks and evaluation
Leaderboards, eval harnesses and ablations — the contested business of deciding which model is actually better.
arXiv AI
Jun 6
Assessing the Geographic Diversity of AI's Platial Representations in Image Generation
arXiv:2606. 05188v1 Announce Type: cross Abstract: (Gen)AI diversity is not merely an ethical issue.
arXiv AI
Jun 6
Dense Contexts Are Hard Contexts: Lexical Density Limits Effective Context in LLMs
arXiv:2606. 06203v1 Announce Type: cross Abstract: Input length and the position of relevant information are widely cited as the primary causes of degraded LLM long-context performance.
arXiv AI
Jun 6
InfoDensity: Rewarding Information-Dense Traces for Efficient Reasoning
arXiv:2603. 17310v2 Announce Type: replace Abstract: Large Language Models (LLMs) with extended reasoning capabilities often generate verbose and redundant reasoning traces, incurring unnecessary computational cost.
arXiv AI
Jun 6
Beyond Waveform Robustness: Robust Feature-Vocoder Adversarial Attacks on Automatic Speech Recognition
arXiv:2606. 05678v1 Announce Type: cross Abstract: Automatic speech recognition (ASR) systems have become widely used for multilingual speech-to-text transcription.
arXiv AI
Jun 6
ATT-CR: Adaptive Triangular Transformer for Cloud Removal
arXiv:2606. 05999v1 Announce Type: cross Abstract: Cloud removal aims to accurately reconstruct the ground objects obscured by clouds in remote sensing images.
arXiv AI
Jun 6
Multi-Granularity Reasoning for Natural Language Inference
arXiv:2606. 05181v1 Announce Type: cross Abstract: Natural Language Inference (NLI) is a fundamental task in natural language understanding that requires determining the logical relationship between a premise and a hypothesis.
arXiv AI
Jun 6
ReTreVal: Reasoning Tree with Validation and Cross-Problem Memory for Large Language Models
arXiv:2601. 02880v2 Announce Type: replace Abstract: Every existing inference-time reasoning framework discards all failure context at problem boundaries, leaving a model solving problem 500 no wiser than it was on problem 1.
arXiv AI
Jun 6
Reducing Hallucinations in Complex Question Answering using Simple Graph-based Retrieval-Augmented Generation (long version)
arXiv:2606. 05901v1 Announce Type: cross Abstract: Large language models (LLMs) have fundamentally transformed the landscape of Natural Language Processing.
arXiv AI
Jun 6
LongSpace: Exploring Long-Horizon Spatial Memory from Perception to Recall in Video
arXiv:2606. 05677v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have advanced image and video understanding and can increasingly handle longer visual inputs.
arXiv AI
Jun 6
LoRi: Low-Rank Distillation for Implicit Reasoning
arXiv:2606. 05315v1 Announce Type: cross Abstract: Implicit chain-of-thought (iCoT) methods aim to internalize reasoning in large language models, but often underperform explicit CoT prompting.
arXiv AI
Jun 6
Edit-R2: Context-Aware Reinforcement Learning for Multi-Turn Image Editing
arXiv:2606. 05950v1 Announce Type: new Abstract: Text-guided image editing has advanced rapidly with diffusion models and unified multimodal foundation models.
arXiv AI
Jun 6
Learning Visual Spatial Planning from Symbolic State via Modality-Gap-Aware Self-Distillation
arXiv:2606. 06076v1 Announce Type: new Abstract: While vision-language models excel at general multimodal understanding, they still struggle with visual spatial planning.
arXiv AI
Jun 6
PC-Talk: Precise Facial Animation Control for Audio-Driven Talking Face Generation
arXiv:2503. 14295v3 Announce Type: replace-cross Abstract: Recent advancements in audio-driven talking face generation have made great progress in lip synchronization.
arXiv AI
Jun 6
SoCRATES: Towards Reliable Automated Evaluation of Proactive LLM Mediation across Domains and Socio-cognitive Variations
arXiv:2606. 05563v1 Announce Type: new Abstract: Evaluating LLM mediators remains challenging, as mediation unfolds as a real-time trajectory shaped by disputants' shifting emotions, intentions, and context.
arXiv AI
Jun 6
ITP-STDP: An Intrinsic-Timing Power-of-Two Learning Engine for On-Chip SNN Training
arXiv:2606. 06159v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) have the potential to emerge as the third generation of neural networks and have attracted increasing attention across a wide range of applications.
arXiv AI
Jun 6
HiDe: Rethinking The Zoom-IN method in High Resolution MLLMs via Hierarchical Decoupling
arXiv:2510. 00054v3 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have made significant strides in visual understanding tasks.
arXiv AI
Jun 6
Benchmarking Open-Source Layout Detection Models for Data Snapshot Extraction from Institutional Documents
arXiv:2606. 06242v1 Announce Type: cross Abstract: Institutional documents contain substantial amounts of operational and analytical information embedded within figures and tables.
arXiv AI
Jun 6
The Mirage of Performance Gains: Why Contrastive Decoding Fails to Mitigate Object Hallucinations in MLLMs?
arXiv:2504. 10020v4 Announce Type: replace-cross Abstract: Contrastive decoding strategies are widely used to reduce object hallucinations in multimodal large language models (MLLMs).
arXiv AI
Jun 6
MAviS: A Multimodal Conversational Assistant For Avian Species
arXiv:2603. 07294v2 Announce Type: replace-cross Abstract: Fine-grained understanding and species-specific multimodal question answering are vital for advancing biodiversity conservation and ecological monitoring.