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- PaperAfter the Federation: Benchmarking Knowledge Portability to Heterogeneous Newcomers
Once historical clients become unavailable, a federation must serve newcomers through the artifact it leaves behind. How much of its knowledge remains useful in an archit
- PaperTamedFlow: Trajectory-Aware Distillation\\for Teacher-Assisted Diffusion Sampling
Diffusion Transformers (DiTs) deliver high-fidelity image and video generation, but inference requires many sequential model evaluations. Two acceleration strategies are
- PaperMultimodal Decoupling for Diversified Recommendation through Semantic and Structural Shaping
Recommender systems often suffer from over-concentrated results when optimized for accuracy, limiting recommendation diversity. While diversity has become an important ob
- PaperFrameGRPO: Incentivizing Video Reasoning via Multi-Frame Rollouts and Temporal Credit
Reinforcement learning with verifiable rewards, particularly Group Relative Policy Optimization (GRPO), has improved video reasoning in multimodal large language models.
- PaperUnderstanding When Reflective Prompt and Skill Optimization Helps on Locally Served Reasoning Models: A Two-Model Study of GEPA and SkillOpt
Reflective text-space optimizers such as GEPA and SkillOpt have reported large gains on frontier and mid-size models. We test replication across two reasoning-native targ
- PaperProtGlycanDock: Towards Accurate Protein-Glycan Docking with Tailored Dataset, Benchmark and Model
Performing accurate protein-glycan docking is critical to understanding protein-glycan interactions which govern many biological processes. However, this important task i
- PaperAccelerated Drift of Scientific Prose in the LLM Era: Evidence from an Interrupted Time-Series Analysis
Every scientific text is embedded in the writing norms of its time: it reflects earlier publications while also shaping the texts that follow. The growing use of LLM-base
- PaperScaling Synthetic Pre-training Data and Evaluation for Indic LLMs
Building capable language models for India requires scalable multilingual data and robust evaluation. We introduce Nemotron-Pretraining-Indic-v1, a synthetic pretraining
- PaperScenario Generalization and Sector Transfer in Real Surface Irrigation Surrogate Modelling with Tabular Models
Surface irrigation planning requires screening many operating conditions and spatial configurations, while high-fidelity shallow-water-equation (SWE) simulations are expe
- PaperCurvature as a Baseline: Monocular Pose Measurement of Cylindrical Objects with Dual Colour Stripe Markers
Thin cylindrical objects offer little space for planar markers. We propose a dual-colour-stripe marker that uses the known curvature of an object to improve pose measurem
- PaperTimesJev: Thinking Fast on Time Series with System 1 Sufficiency
Large language models (LLMs) have recently shown strong potential for time series reasoning, while models that reason over time series are usually with long chains of tho
- PaperSPLASH: Contrastive Audit Pressure for Detecting and Localizing Security Hallucinations in Generated Code
Code generated by large language models often passes every functional test while remaining insecure. These security hallucinations are common, written with high confidenc
- PaperPnP-CF: A Consensus Flow-Matching Solver for General Inverse Problems
Plug-and-Play (PnP) methods using continuous-time deep generative models as learned data distribution priors enable synthesizing high-quality solutions of model-based inv
- PaperTempoMoE: Identifying and Steering Fast-Slow Thinking Experts for Efficient Multimodal Reasoning
Multimodal Mixture-of-Experts (MoE) reasoning models rely on long chain-of-thought (CoT) for complex tasks, yet often overthink easy inputs, increasing token cost and lat
- PaperInternalizing Chain-of-thought into Looped Transformers
Chain-of-thought (CoT) enables constant-bit-size transformers to perform general-purpose computation through generated tokens (Li and Wang, 2025a), whereas looped transfo
- PaperFederated Community Detection in Bipartite Networks
We study federated spectral estimation when a large matrix is horizontally partitioned across servers that cannot share raw data. We propose FLICKER, a target-specific gr
- PaperProcedural Memory for Language Agents: A Neurosymbolic Perspective on Explicit Goal Structure
Large language models remain unreliable on long-horizon tasks requiring procedural reasoning. We argue that a key cause is the absence of explicit procedural memory: acce
- PaperGraph-to-Table Interfaces Control Relational Generalisation
Graph-to-table systems combine three design choices: an encoder that maps relational evidence to feature rows, a context constructor that selects labelled examples, and a
- PaperMap-Distribution Mixture-of-Experts for Multi-Agent Pathfinding
Designing capable neural policies for multi-agent pathfinding (MAPF), which map local observations to action distributions, represents an important challenge in multi-age
- PaperNIOCIS: Typed-Decision Next-Hop Routing with Node-Conditioned Option Spaces for Tool-Use Agents
Tool-use agents pay per decision: at each hop a language model re-reads the state and thinks for seconds, though its actions are finite and decisions recur. We present NI
- PaperAuditor-Assisted Summary-Channel Verification for Hosted LLM Identity Substitution
Hosted LLM services increasingly expose model identity as a product claim, but external users and auditors often cannot inspect which model configuration served a request
- PaperClueFlow: Learning Long-Horizon Search through Attributed Research-State Transitions
Long-horizon search requires agents to acquire relevant evidence and integrate it into an evolving research state. Existing methods maintain research states to guide expl
- PaperGraphEvoResearcher: Graph-Aware Training-Free Self-Reflective Reasoning for Cost-Bounded Multi-Hop Question Answering
Multi-hop question answering (QA) requires models to chain intermediate conclusions while remaining cost-aware. Existing training-free self-reflective protocols (generate
- PaperOn the Benefits of Uncertainty Estimation for Species Classification: A Case Study on Optimizing Expert re-Annotation
Automated identification of diatoms from microscopic images is a cornerstone of large-scale freshwater biomonitoring, yet the high diversity of species and strong class i
- PaperCorrectness-Dependent Asymmetric Target Distributions for Self-Distillation Policy Optimization
Self-distillation policy optimization provides dense token-level supervision for LLM post-training through feedback-conditioned self-teachers. However, directly matching
- PaperGLOBE: Geometry-Led Online Behavioral Early Exit via Unit-Sphere Trajectories
Chain-of-thought (CoT) reasoning can improve problem solving, but models often keep generating after the correct answer is already reachable; the extra steps raise servin
- PaperReconstruction and Discrete-Event Simulation Assessment of an Analytical
This article presents an analytical-DES benchmark for intra-aisle robotic picking in automated warehousing. The investigated cycle combines horizontal shuttle travel, tot
- PaperBehavioral Probes for Information Flow in LLM Swarms
Most existing approaches to LLM swarm optimization are utility-driven, focusing on final task utility while leaving the processing, integration, and reliance of informati
- PaperToken-Set Choice Confounds POPE: A Systematic Audit of Yes/No Extraction in VLM Hallucination Evaluation
We set out to reproduce a recent hallucination-mitigation result on the POPE benchmark. The LLaVA-1.5-7B baseline we measured, 82.21 F1 on the adversarial split, sat 1.21
- PaperABACUS: Program-Guided Multistep Reasoning over Frozen Judgment Models
Judgment models answer semantic questions by scoring a finite set of candidate outcomes. Can reusable programs turn these local decisions into powerful multistep reasonin
- PaperPaceVLA: Adaptive Temporal Action Quantization in Vision-Language-Action Models
Fast and reliable manipulation is crucial for practical robot deployment. Although Vision-Language-Action (VLA) models have recently shown remarkable progress as generali
- PaperHORIA: 4D Human and Object Reconstruction from a Monocular Video with Interaction-Aware Re-Rendering
Joint 4D reconstruction of a human and object from a monocular video is essential for understanding how people interact with their environment. While recent methods have
- PaperEmbodiedWorld-200K: Toward Embodied World Agents via Embodied-Planning Dataset and Interactive World Models
Building embodied agents that can perceive, reason, and act across diverse 3D worlds is a central research direction toward artificial general intelligence. Yet most exis
- PaperProductive State-Space Exploration for Multi-turn RL in LLM Agents
Reinforcement Learning (RL) for Large Language Model (LLM) agents in multi-turn, long-horizon environments remains challenging due to inefficient action selection and rep
- PaperCXBench: A Benchmark for Process-Compliant LLM Agents in Regulated Customer-Experience Workflows
Tool-using language agents increasingly perform regulated customer-service workflows, where a correct final state is insufficient: agents must also provide disclosures, o
- PaperAdaExploreBench: Benchmarking LLM Agents for Proactive Exploration and Test-time Adaptation in Evolving Environments
Large Language Model (LLM) agents are increasingly deployed in unfamiliar and evolving environments, requiring them to proactively explore, understand, and adapt to envir
- PaperOrderGPT: Generation Order as a Learnable Modeling Choice
Generative modeling of discrete data has two popular paradigms: autoregressive models such as GPT, which factorize a sequence in a left-to-right (L2R) order, and masked d
- PaperClaim Laundering: When Agent Decision Models Trust Records Over Reality
Agent decision models select actions in a single forward pass from inputs that combine environmental observations with the agent's own record of previous actions. When an
- PaperPolicy Search in Code Space for Multi-Agent Pathfinding
Developing coordination policies for complex multi-agent systems relies on either labor-intensive algorithm design or opaque task-specific reinforcement learning. With re
- PaperSpeech LLMs That Breathe: Modeling Non-Verbal Vocalizations in Dialogue
The user experience of speech interaction models has improved, benefiting from the modeling of paralinguistic attributes and advances in speech reconstruction paradigms.
Headlines and links come from the labs' own blogs, Hacker News and the GDELT news index, and from the sources our index already follows. We show a short excerpt and always link to the original. A launch reported by a news site rather than the lab is marked “Reported” until the lab itself announces it.