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arXiv:2608.20729v1 Announce Type: new Abstract: Language-model agents can improve after failure or carry text across episodes without revising what counts as success. We study the narrower attribution

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Model Releases

Can Legal AI Know When It Is Wrong? And Do Students Know When It Is?

DGX agent

arXiv:2608.21089v1 Announce Type: new Abstract: Integrating Large Language Models (LLMs) into the Indian judiciary promises access to justice but introduces severe risks. We identify the 'inertia of c

model-releasesarxiv-cs-ai

24 Aug 2026

Tutorials

Decoupled Vision-Language System for Multimodal Understanding and Generation

arXiv:2608.20382v1 Announce Type: new Abstract: We introduce a new architecture design for multimodal large language models (MLLMs), Libra, capable of both multimodal understanding and generation. Lib

tutorialsarxiv-cs-cl

Do SpeechLMs Hear Their Own Opinions? Diagnosing and Mitigating Previous-Belief Contamination in Streaming Emotion Understanding

arXiv:2608.20769v1 Announce Type: cross Abstract: Streaming emotion understanding uses historical state while continuously interpreting current audio, often feeding the model's previous prediction bac

Fine-tuning LLMs for Tourist Trajectory Prediction using Field Experiment Data

arXiv:2608.20830v1 Announce Type: cross Abstract: Evaluating mobility interventions at tourist destinations requires predicting visitor behavior under varying conditions. Traditional methods struggle

Is Visual Prompting All You Need? Studying VLM Spatial Reasoning under Progressive Visual Scaffolds

arXiv:2608.21170v1 Announce Type: cross Abstract: Vision-language models (VLMs) have advanced rapidly in multimodal reasoning, yet recent work shows that their failures often reflect an interaction be

MeltwaterBench: Deep learning for spatiotemporal downscaling of surface meltwater

arXiv:2512.12142v2 Announce Type: replace-cross Abstract: The Greenland ice sheet is melting at an accelerated rate due to processes that are not fully understood and hard to measure. The distribution

Move by Move: Measuring and Steering How LLMs Conduct Psychotherapy

arXiv:2608.21325v1 Announce Type: new Abstract: Users increasingly turn to large language models for emotional support, yet little is known about how these models actually conduct a psychotherapy inte

safetyarxiv-cs-cl

SKILL-RAG: Self-Knowledge Induced Learning and Filtering for Retrieval-Augmented Generation

arXiv:2509.20377v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has significantly improved the performance of large language models (LLMs) on knowledge-intensive tasks i

researcharxiv-cs-ai

SPARK-SAM: Self-Prompt Adaptation with Response Knowledge for SAM in Infrared Small Target Segmentation

arXiv:2608.20754v1 Announce Type: new Abstract: Promptable segmentation models provide a reusable interface, but direct transfer to automatic infrared small-target segmentation (IRSTD) exposes a misma

Stored in Optimizer State, Valued by Later Training: A Causal Account of Subliminal Trait Transfer

arXiv:2608.20442v1 Announce Type: new Abstract: Subliminal trait transfer allows a student model to acquire behavioral dispositions from teacher-generated data in which the trait is not semantically e

Toward Auto-Research: Mining Falsifiable Research Ideas from Paper Knowledge Graphs with Categorical Structure

arXiv:2608.20361v1 Announce Type: cross Abstract: Automated research-idea generation systems built on large language models (LLMs) share a structural weakness: they reduce ideation to free-text recomb

researcharxiv-cs-ai

ArmorOCR: Grounded Adversarial Visual Perception via Observation-Transferred Self-Distillation

arXiv:2608.20122v1 Announce Type: new Abstract: Large multimodal models (LMMs) have demonstrated strong OCR recognition capabilities, yet remain vulnerable to adversarial visual text that is readable

BeyondMasks: Evaluating Causal and Physical Consistency in Video Object Removal

arXiv:2608.20107v1 Announce Type: new Abstract: Recent advances in generative video models have significantly improved visual realism in video object removal, yet evaluation protocols still focus on m

Computational Phenomenology of Borderline Personality Disorder: A Comparative Evaluation of LLM-Simulated Expert Personas and Human Clinical Experts

arXiv:2508.19008v3 Announce Type: replace Abstract: Building on a human-led thematic analysis of clinical life-story interviews (> 150,000 words) with inpatients with Borderline Personality Disorder,

Evidence Before Expansion: Reuse, Spawn, or Defer in Lifelong Expert Pools

arXiv:2608.19888v1 Announce Type: cross Abstract: Streaming systems that maintain a pool of expert models must repeatedly decide whether to reuse an existing expert for arriving data, spawn a new one,

Gravitational-wave parameter estimation with machine-learning generated surrogate waveforms

arXiv:2608.20222v1 Announce Type: cross Abstract: The worldwide network of gravitational-wave detectors have detected more than 350 binary coalescence events till date. Future third-generation detecto

Manifold Drift in Flow Preference Optimization: A Root Cause of Reward Hacking

arXiv:2608.20011v1 Announce Type: new Abstract: Preference optimization is a standard alignment method for generative models, yet extending it to continuous-time dynamics remains non-trivial. In flow

Mechanistic Tomography: Designed Measurement for Control-Oriented Interpretability

arXiv:2608.19338v1 Announce Type: cross Abstract: Mechanistic interpretability seeks quantities that models do not expose directly: represented states, component effects, interactions, and responses t

Systematic Evaluation of TabPFN-TS for Zero-Shot Probabilistic Heat Load Forecasting in District Heating Networks

arXiv:2608.20024v1 Announce Type: new Abstract: District heating energy hubs require reliable heat load forecasts for efficient operational scheduling. Conventional forecasting workflows train system-

researcharxiv-cs-lg

Applications

Teacher-free Latent Self-distillation and Class-separable Representations for Lightweight IoT Attack Detection

arXiv:2403.15509v3 Announce Type: replace-cross Abstract: Knowledge distillation (KD) has been widely used to improve lightweight AI models by transferring soft-label knowledge from a large teacher mo

applicationsarxiv-cs-ai

V-REX: Efficient Specialist VLM Training for Veterinary X-Rays

arXiv:2608.20069v1 Announce Type: new Abstract: While generalist VLMs are expensive to train, creating domain experts is widely assumed to require fine-tuning increasingly large foundation models. We

researcharxiv-cs-cv

What Matters for Latent Actions in Robot Learning

arXiv:2608.19613v1 Announce Type: cross Abstract: Latent Action Models (LAMs) have emerged as a promising paradigm for enabling robot learning to leverage large-scale unlabeled videos through latent a

safetyarxiv-cs-cv

When Contextual Inference Fails: Cancelability in Interactive Instruction Following

arXiv:2603.19997v2 Announce Type: replace Abstract: We investigate the separation of literal interpretation from contextual inference in a collaborative block-building tasks, where an agent must resol

Local Ai

Write Once, Run Everywhere: The Axon DSL for Shape-Safe and Framework-Agnostic LLM Architectures

arXiv:2608.19889v1 Announce Type: new Abstract: The entire ecosystem of open-source language models effectively relies on a single platform. What if this platform was forced to shut down tomorrow? Imp

local-aiarxiv-cs-ai

Beyond the Transcript: Detecting Covert Co ordination in Latent Multi-Agent Communication

arXiv:2608.19161v1 Announce Type: new Abstract: Language-model agents can communicate through continuous hidden states that are invisible in public transcripts, creating opportunities for covert harmf

Bidirectional representational alignment between biological and artificial neural networks

arXiv:2608.18244v1 Announce Type: cross Abstract: Recent work has shown that representational alignment between biological and artificial neural networks is asymmetric: model representations predict n

safetyarxiv-cs-ai

ClosureBench: A Constructive Benchmark for Compositional Graph Reasoning

arXiv:2608.18242v1 Announce Type: new Abstract: We introduce ClosureBench, a constructive benchmark for compositional graph-relational reasoning with programmatically verified ground truth. Unlike fix

Comment-level Topic Drift Analysis in the Reddit Corpus

arXiv:2608.19133v1 Announce Type: new Abstract: We present a novel application of embedding-based dynamic topic modeling techniques to detect and quantify topic drift at the comment level in a massive

researcharxiv-cs-cl

ERASE: EaRly bAckpropagation SchEdule for Faster Training of Modern Recommendation Systems

arXiv:2608.18469v1 Announce Type: cross Abstract: Lightweight proxy models enable rapid experimentation without repeatedly training frontier-scale systems, but their small kernels often leave modern a

Figurative and Cultural Knowledge in LLMs: Investigating Cross-Domain Transfer through Fine-Tuning

arXiv:2608.18361v1 Announce Type: new Abstract: Figurative language is deeply culturally embedded; fluent use requires not just linguistic competence but cultural immersion. We ask whether LLMs can le

FiLoRA: Focus-and-Ignore LoRA for Controllable Feature Reliance

arXiv:2602.02060v2 Announce Type: replace-cross Abstract: Multimodal foundation models integrate heterogeneous signals across modalities, yet it remains unclear whether their predictions can be contro

Grading the Graders: Verification Autonomy Levels (L0-L5) for LLM Reasoning

arXiv:2608.19009v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly paired with verifiers (step checkers, self-consistency filters, tool-based fact checkers, formal proof ass

Applications

GraphK: Variable-Size Graph Generation with Efficient Edge Construction

arXiv:2608.18777v1 Announce Type: new Abstract: Graph generation models have advanced significantly with deep learning, yet they remain limited in scalability, flexibility, and ability to model underl

applicationsarxiv-cs-lg

Jailbreaking in the Haystack

arXiv:2511.04707v2 Announce Type: replace-cross Abstract: Recent advances in long-context language models (LMs) have enabled million-token inputs, expanding their capabilities across complex tasks lik

Latent Space Refusal Anchoring for Low-Resource African Languages: Mechanistic Safety Recovery Without Retraining

arXiv:2608.18089v1 Announce Type: cross Abstract: Instruction-tuned models often refuse harmful requests in English but comply with the same requests in Yoruba, Igbo, Igala, and Hausa. This suggests t

Multimodal Rapport Estimation in Real-World HRI

arXiv:2608.18401v1 Announce Type: cross Abstract: Evaluating interaction quality in real-world HRI is an important challenge. If interaction quality can be estimated reliably, the results can be used

Persona-Guided LLM Agents for Task-Oriented Dialogue

arXiv:2608.18085v1 Announce Type: new Abstract: Prior work has shown that large language models (LLMs) can express diverse personality traits in open-ended text generation. However, it remains unclear

Position: Profiling Game Worlds by Transition Complexity

arXiv:2608.18079v1 Announce Type: new Abstract: Game world modeling (GWM) and reinforcement learning (RL) are often confounded because research papers rarely quantify how difficult the underlying tran

Same Facts, Different Updates: Inference Setup Shapes LLM Behavior in Medical Allocation

arXiv:2608.18108v1 Announce Type: cross Abstract: Large language models are being incorporated into sensitive and important decision-making processes across nearly all fields. While prior work studies

safetyarxiv-cs-ai

Task-Conditioned Least-Privilege Learning for Executable Terminal and MCP Agents

arXiv:2608.18351v1 Announce Type: cross Abstract: Tool-using large language-model agents can complete a task while exercising authority that the user did not grant or the task does not need, causing e

VTONQA: A Multi-Dimensional Quality Assessment Dataset for Virtual Try-on

arXiv:2601.02945v2 Announce Type: replace Abstract: With the rapid development of e-commerce and digital fashion, image-based virtual try-on (VTON) has attracted increasing attention. However, existin

Certified but Private: Scalable Zero-Knowledge Proofs for Neural Network Guarantees

arXiv:2608.17070v1 Announce Type: new Abstract: With the growing deployment of machine learning models, formal guarantees of the robustness and fairness of these models have become increasingly import

safetyarxiv-cs-lg

CKAA: Cross-subspace Knowledge Alignment and Aggregation for Robust Continual Learning

arXiv:2507.09471v2 Announce Type: replace Abstract: Continual Learning (CL) empowers AI models to continuously learn from sequential task streams. Recently, parameter-efficient fine-tuning (PEFT)-base

Encoded but Not Actionable: Auditing the Decode-Generate-Steer Gap in Frozen LLMs for Geometric Constraints

arXiv:2608.17843v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong performance on structured reasoning tasks, but what they encode and whether it informs model beh

researcharxiv-cs-ai

Foundation Agents Meet Agentic Deep Research: Evidence-Grounded Clinical Code Forecasting

arXiv:2608.17075v1 Announce Type: cross Abstract: Next-encounter ICD forecasting predicts which standardized diagnosis codes will be documented at a future visit from the longitudinal record available

Local Ai

Predicting Male Domestic Violence Using Explainable Ensemble Learning and Exploratory Data Analysis

arXiv:2403.15594v4 Announce Type: replace-cross Abstract: Domestic violence is commonly viewed as a gendered issue that primarily affects women, which tends to leave male victims largely overlooked. T

local-aiarxiv-cs-lg

SE-MoLoRA: Shared-Expert LoRA Adapters for Domain-Specific Photographic Assessment

arXiv:2608.17514v1 Announce Type: new Abstract: Vision-language models can describe images fluently, but they often fail to provide actionable photographic critique because semantic content and aesthe