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arXiv:2608.29066v1 Announce Type: cross Abstract: Stance detection is crucial for understanding the underlying attitude of an expression towards a target. Conversational stance detection is a more cha

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Model Releases

Phonely launches Alma, a voice AI model trained on 10M+ phone conversations

DGX agent

Phonely Ltd. today announced the launch of Alma, a large language artificial intelligence model built for voice agents, trained on more than 10 million real phone conversations. The company said many

model-releasessiliconangle

1 Sept 2026

PhysVR: Vision-Language Model Guided Interference-aware Temporal Feature Refinement for Remote Physiological Measurement

arXiv:2608.29663v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables contactless physiological measurement from facial videos, yet its subtle pulse-related variations are easily

local-aiarxiv-cs-cv

PLC-DPO: Posterior Label Correction in Noisy and Ambiguous Preference Optimization

arXiv:2608.30597v1 Announce Type: cross Abstract: Direct Preference Optimization (DPO) simplifies alignment through pairwise comparisons but assumes all observed preferences are reliable. Real data of

Safety

Popular but Wrong: Understanding and Mitigating LLM Overconfidence through Knowledge Popularity

arXiv:2505.17537v2 Announce Type: replace Abstract: Large language models (LLMs) often produce incorrect answers with high confidence, yet the factors associated with such overconfidence remain insuff

safetyarxiv-cs-cl

Tutorials

Predicting the Unpredictable: LLM-powered Long-term Chaotic Time Series Forecasting under Short-term Observations

arXiv:2608.29579v1 Announce Type: new Abstract: Chaotic time series forecasting is a challenging task due to its sensitivity to initial conditions and long-term unpredictability. Traditional methods t

tutorialsarxiv-cs-lg

Tutorials

Pretrained, Curriculum-Tuned, and Ensembled: A Tracer-Aware Interactive Segmentation Pipeline for AutoPET V

arXiv:2608.30844v1 Announce Type: cross Abstract: Interactive lesion segmentation in whole-body PET/CT requires a model to provide a strong initial prediction while also responding efficiently to spar

tutorialsarxiv-cs-ai

ProGS: Towards Progressive Coding for 3D Gaussian Splatting

arXiv:2603.09703v2 Announce Type: replace Abstract: Progressive transmission of 3D Gaussian Splatting (3DGS) requires each completed transmission stage to be decodable from received data and directly

Quantitative Evidence Mining for Plausibility-Aware Biomedical AI

arXiv:2608.30393v1 Announce Type: new Abstract: Biomedical artificial intelligence (AI) systems increasingly extract, organize, and reuse scientific claims from literature, clinical trials, and regula

agentsarxiv-cs-cl

Question: Why is prefill unbelievably faster in vLLM than other inference engines?

I only started using some vLLM forks recently in a 4 x 48GB 4090 system. DS4F - ~5000pp/180tg (DSpark) Qwen3.8 Flash next - ~7500pp/135tg (MTP) This is amazing, like having the API in my house. But it

Safety

Review Before Trust: Source-Grounded Integrity Gates for AI-Assisted Personal Health Records

arXiv:2608.29965v1 Announce Type: new Abstract: Large language models can convert medical documents into structured data, but plausible output may still be unsupported by the source. Persisting such o

safetyarxiv-cs-ai

RIDGE: Region-Informed Derivative-Guided Evidence Selection for Long Video Understanding

arXiv:2608.29958v1 Announce Type: new Abstract: Long videos contain far more visual content than Large Vision-Language Models (LVLMs) can process under a fixed visual-token budget, making frame select

S3C-LLM: Skill-Code Guided Agentic Language Models for Spectrum-to-Structure Elucidation

arXiv:2608.30910v1 Announce Type: cross Abstract: Spectroscopic structure elucidation is central to molecular analysis, but recent Large Language Model (LLM)-based methods mostly formulate it as direc

agentsarxiv-cs-cl

SafeAtlas-VL: Beyond Binary Multimodal Safety with Large-Scale Data and Guard Models

model-releasesarxiv-cs-ai

arXiv:2608.29098v1 Announce Type: new Abstract: Multimodal safety moderation requires distinguishing risks arising from visual content, user intent, and assistant behavior. Existing safeguards, howeve

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

model-releasesarxiv-cs-ai

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

Test-Time Training with Next-Token Prediction

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

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

TRIPPULSE: Multi-Agent Travel Planning with Review-Grounded Reasoning

arXiv:2608.30924v1 Announce Type: new Abstract: Travel itinerary generation requires balancing strict spatio-temporal constraints with human preferences. Existing LLM-based planners mainly rely on str

local-aiarxiv-cs-cl

Unified-MAS: Universally Generating Domain-Specific Nodes for Empowering Automatic Multi-Agent Systems

arXiv:2603.21475v2 Announce Type: replace Abstract: Automatic Multi-Agent Systems (MAS) generation has emerged as a promising paradigm for solving complex reasoning tasks. However, existing frameworks

agentsarxiv-cs-ai

VCAR: Training-Free 3DGS Segmentation via View Completeness and Axis-Aware Boundary Refinement

arXiv:2608.30870v1 Announce Type: new Abstract: Semantic segmentation in 3D Gaussian Splatting (3DGS) is crucial for advancing 3D scene understanding. Existing methods predominantly rely on feature di

Vectors from Larger Language Models Predict Human Reading Time and fMRI Data More Poorly when Dimensionality Expansion is Controlled

arXiv:2505.12196v2 Announce Type: replace Abstract: The impressive linguistic abilities of large language models (LLMs) have recommended them as models of human sentence processing, with some conjectu

View-oriented Conversation Compiler for Agent Trace Analysis

arXiv:2603.29678v3 Announce Type: replace Abstract: We observe that an agent trace is a structured document. A coding agent session contains user turns, assistant text, chain of thought blocks, tool c

agentsarxiv-cs-ai

Weaving Visual Narratives: Agentic Image Bundle Composition Beyond Atomic Visual Matching

model-releasesarxiv-cs-cv

arXiv:2608.28695v1 Announce Type: new Abstract: Image retrieval has traditionally been formulated as a point-wise matching problem, where each candidate image is scored in isolation. However, this ato

Where Induction Runs Out: Description-Length Difficulty and the Memorisation Gap in Integer-Sequence Benchmarks

model-releasesarxiv-cs-lg

arXiv:2608.29411v1 Announce Type: new Abstract: Integer sequences from the On-Line Encyclopedia of Integer Sequences (OEIS) are increasingly used to benchmark mathematical reasoning in language models

Whole-Slide Image Analysis under Realistic Few-Shot Annotation Protocols

arXiv:2608.30420v1 Announce Type: cross Abstract: Automating the analysis of whole-slide images has high clinical value, since characterizing cancers requires examining them in detail. Such analysis i

local-aiarxiv-cs-ai

Safety

You Shouldn't Have Asked: A Pragmatics-Inspired Taxonomy for Evaluating LLM Refusals

arXiv:2608.30856v1 Announce Type: new Abstract: Refusals are often treated as face-threatening acts in pragmatics because they can challenge the requester's socially claimed self-image. Large language

safetyarxiv-cs-cl

A Formal Limitation on Learning Human Language From Textual Corpora

arXiv:2608.28560v1 Announce Type: new Abstract: Can a listener recover what a speaker means from the form of an utterance alone? We answer this question information-theoretically, and for a listener g

Applications

Actionable CBFI: Integrating Structural Decomposition and Causal Counterfactual Recourse for Tabular Machine Learning

arXiv:2608.27821v1 Announce Type: new Abstract: Explainable artificial intelligence (XAI) increasingly calls for actionable counterfactual recourse, yet current methodologies face challenges related t

applicationsarxiv-cs-lg

Diffusion Distillation for Efficient Weather Ensembles

arXiv:2608.27728v1 Announce Type: new Abstract: Diffusion models generate skillful weather ensembles but require costly iterative sampling. We introduce a supervised energy-distance distillation metho

researcharxiv-cs-lg

Entity-Memory Graph Retrieval Improves Evidence Coverage in Long-Conversation Question Answering

arXiv:2608.27925v1 Announce Type: new Abstract: Entity-Memory graph retrieval keeps dialogue turns as verbatim Memory nodes, links repeated mentions through shared Entities, and connects adjacent Memo

GeoFF3D: Coordinate-Anchored Feed-Forward Reconstruction for Large-Scale UAV Mapping

arXiv:2608.28288v1 Announce Type: new Abstract: Existing feed-forward 3D reconstruction methods typically process a bounded number of images and recover cameras and geometry in local or internally nor

local-aiarxiv-cs-cv

How I got Qwen 3.8 27b running at ~75t/s decode on 16GB RTX 5080

Hi all, I have recently been experimenting with different LLM set ups and after everyone was raving about how good Qwen 3.8 27b was, I was inspired to try and get it deploying. After some battling wit

Ladders in Chaos: When, How, (and Perhaps Why) Does Test-Time Scaling Improve LLM Machine Translation

arXiv:2608.28496v1 Announce Type: new Abstract: Two forms of test-time scaling for Large Language Models (LLMs) have emerged as effective and widely adopted paradigms: sequential, in which later answe

Learning a Single Token to Replace Long System Prompts in LLMs

arXiv:2511.23271v2 Announce Type: replace Abstract: Long system prompts are widely used to steer Large Language Models (LLMs), but repeatedly processing them at inference time is inefficient and consu

Learning to Difference: Adaptive Reversible Differencing (AdaRDiff) for Time Series Forecasting

model-releasesarxiv-cs-lg

arXiv:2608.28134v1 Announce Type: new Abstract: Reliable long-horizon time series forecasting is an important yet difficult problem. Trends and seasonality introduce complex temporal structure that ch

Most agent tutorials stop before the hard parts. This one builds them step by step. Deep Agents from Scratch is a five-notebook LangGraph co…

Most agent tutorials stop before the hard parts. This one builds them step by step. Deep Agents from Scratch is a five-notebook LangGraph course for builders who want to understand how advanced AI age

agentsharrison-chase--x

Qwen3.8-Flash-Next-NVFP4 vs Qwen3.8-27B-FP Test Results

## Qwen3.8-Flash-Next-NVFP4 (inferact) vs Qwen3.8-27B-FP8 (qwen) Slammed with work and no time to pretty this up. Qwen wrote most of this but I checked the data. All tests done on the same rig, same p

Semantic Head Specialization Guides Hybrid ViT Attention for Multimodal LLMs

arXiv:2608.28383v1 Announce Type: cross Abstract: Hybrid attention dominates frontier LLMs, yet Vision Transformers (ViTs) in multimodal LLMs lack a satisfactory hybrid design, with no consensus on wh

Spectral Query-Key Product Weight Steering for Training-Free VLM Hallucination Mitigation

arXiv:2606.20419v2 Announce Type: replace Abstract: Vision-language models (VLMs) often generate fluent but visually unsupported descriptions, especially by mentioning objects absent from the image. W

local-aiarxiv-cs-cv

Stranger, Fan, or Peer? A Systematic Study on the Role of Interlocutor in Persona-Based Dialogue Generation

arXiv:2608.28467v1 Announce Type: new Abstract: Persona-based dialogue systems are usually conditioned on speaker biography, but dialogues involve at least two participants, and who has access to whos

Task-State Adaptation with Prototype Memory for Multi-Task Dense Prediction

arXiv:2608.28078v1 Announce Type: new Abstract: Vision foundation backbones provide strong representations for dense prediction, yet a single shared feature still needs to support tasks with different

Applications

Thanks @juliafedorin for a great conversation! Some tidbits from the podcast on the AI space: - We've pivoted from building a RAG framework …

Thanks @juliafedorin for a great conversation! Some tidbits from the podcast on the AI space: - We've pivoted from building a RAG framework towards building the document infrastructure for agents - Do

applicationsjerry-liu--x

The Chrono Trigger plot challenge - Crono awakens in his modest bedroom of 2095...

A hallucinated event, Crono awakens in his modest bedroom of 2095... I am using local models since 2025 January. My daily driver is qwen 3.6 35B A3B, which works pretty well for coding tasks, but I al

What Do Interaction Representations Actually Measure? Pre-Event Separability in Weakly-Supervised Violence Detection

model-releasesarxiv-cs-cv

arXiv:2608.27879v1 Announce Type: new Abstract: Articulated human pose provides detailed body-configuration information beyond coarse spatial relationships, but whether this detail yields greater disc

What Will This Copper Look Like Later? Forecasting Surface Appearance and Rendering It as a PBR Material

model-releasesarxiv-cs-cv

arXiv:2608.28102v1 Announce Type: cross Abstract: Digital design requires predicting how a metal surface will look later in its oxidation; this paper presents such a pipeline for copper. Given a fixed

Are there any interesting architectural innovations that we seem to be on the verge of for LLM models or AI models that might be a big deal? (Excluding maybe N-gram, since everyone is already well aware of that one)

So, ideally for this thread we exclude the ones that everyone on here is already well aware of and discussing on here a lot, like N-gram, quantization improvements, MTP, D-flash, and D-spark, since th

local-air-localllama

30 Aug 2026

Calculate --override-tensor for llama.cpp using QWEN models and Pi for 2 GPU

When using two GPU with llama.cpp with --split-mode layer you usually provide a --tensor-split value to fit the proportion of the allocation on each GPU, say you have 16GB + 12GB something like --tens

30 Aug 2026

Industry

Patterns in 'Woman' Image Generation