AI15 min read
ArXiv limits submissions to two per month due to AI paper flood
ArXiv now caps submissions to two papers per person per month because AI tools have driven monthly submissions past 40,000.
From The Decoder
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AI15 min read
ArXiv now caps submissions to two papers per person per month because AI tools have driven monthly submissions past 40,000.
From The Decoder
LLMs1 min read
A discrete diffusion framework enables parallel refinement of multiple target languages with sublinear latency scaling. It achieves comparable quality to autoregressive baselines while supporting zero-shot transfer to unseen source languages.
From arXiv cs.CL
Photo: Yan Krukau
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Researchers propose NarraLite, a framework for multimodal generative recommendation that compresses visual contexts and uses latent reasoning tokens. The system improves narrative coherence in short-form drama continuation while reducing redundant computation.
From arXiv cs.CL
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Researchers propose MIMIC, a framework using executable code to synthesize high-fidelity reasoning data. Training on this dataset improves accuracy across general reasoning and mathematical benchmarks.
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From arXiv cs.CL
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A new paradigm named State of Thought (SoT) uses a compact controller to activate historical reasoning support based on internal model states, improving accuracy while reducing tokens and latency.
From arXiv cs.CL
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Researchers propose REALM, a framework using retrieval feedback to reorganize long-term memory in LLM agents. It achieves 75.97% accuracy on LoCoMo and 65.11% on LongMemEval.
From arXiv cs.CL
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A new paper formalizes state mutability to address semantic shadowing in RAG, introducing GC-Mem which recovers over 90% conflict resolution accuracy.
From arXiv cs.CL
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arXiv:2609.13470v1 Announce Type: new Abstract: Although large language models (LLMs) have demonstrated remarkable capabilities, their reliance on cloud-scale infrastructure poses fundamental challenges for deployment in agentic pipeline...
From arXiv cs.AI
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arXiv:2609.13580v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities across a wide range of natural language processing tasks. However, conventional fine-tuning typically relies on centralize...
From arXiv cs.AI
Research1 min read
arXiv:2609.13552v1 Announce Type: new Abstract: Generative AI is increasingly being used informally in Air Traffic Management (ATM) for tasks such as flight plan generation, trajectory interpretation, and constraint checking. Although th...
From arXiv cs.AI
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arXiv:2609.13566v1 Announce Type: new Abstract: Industrial maintenance systems involve multiple interacting assets and shared resources, making it challenging to balance reliability and operational cost using a single decision framework....
From arXiv cs.AI
Research1 min read
arXiv:2609.13396v1 Announce Type: new Abstract: Multi-objective Bayesian optimisation (MOBO) is a sample-efficient approach for optimising expensive black-box functions with multiple objectives. In MOBO, the goal is to adequately approxi...
From arXiv cs.AI
Research1 min read
arXiv:2609.13356v1 Announce Type: new Abstract: In this work, we present ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, system, and algorithmic efficiency. ZGCM-1 is founded on a core premise: comp...
From arXiv cs.AI
Research1 min read
arXiv:2609.13602v1 Announce Type: new Abstract: Voice agents often need to collect names, addresses, identifiers, dates, and times exactly, yet end-to-end benchmarks obscure where capture fails. We introduce $\tau$-Elicitation, a 200-tas...
From arXiv cs.AI
Research1 min read
arXiv:2609.13548v1 Announce Type: new Abstract: Web agents can utilize reusable tools to reduce the cost and latency of low-level browser interaction, but automatically discovered tool collections can be large, redundant, and poorly alig...
From arXiv cs.AI
LLMs1 min read
arXiv:2609.13582v1 Announce Type: new Abstract: A clinical agent benchmark can report the same verdict on identical inputs while the agent files a materially different order on each run. Such agents order tests, request medications and p...
From arXiv cs.CL
Research1 min read
arXiv:2609.13422v1 Announce Type: new Abstract: LLM judges are increasingly used to evaluate and improve AI-generated outputs, yet their reliability for complex professional work remains unclear. We study this problem through Vibe Patent...
From arXiv cs.AI
Research1 min read
arXiv:2609.13466v1 Announce Type: new Abstract: Enterprise AI adoption has reached 78% of organizations globally, yet the infrastructure to govern that adoption has not kept pace. This paper identifies and characterizes the attestation d...
From arXiv cs.AI
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