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From the 1 of 16 linked papers with an AI index.

most citedAutoResearchBench: Benchmarking AI Agents on Complex Scientific Literature Discovery

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cs.CL2026

Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent

Lei Bai, Zongsheng Cao, Yang Chen +50

The paper introduces Agents-A1, a 35B mixture-of-experts agent model that attains trillion-parameter-level performance by extending the length of reasoning horizons and integrating…

cs.CL2026

DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

DeepSeek-AI, Anyi Xu, Bangcai Lin +315

We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…

cs.CL2026

MTRouter: Cost-Aware Multi-Turn LLM Routing with History-Model Joint Embeddings

Yiqun Zhang, Hao Li, Zihan Wang +6

Multi-turn, long-horizon tasks are increasingly common for large language models (LLMs), but solving them typically requires many sequential model invocations, accumulating substan…

cs.CL2026

MultiPress: A Multi-Agent Framework for Interpretable Multimodal News Classification

Tailong Luo, Hao Li, Rong Fu +7

With the growing prevalence of multimodal news content, effective news topic classification demands models capable of jointly understanding and reasoning over heterogeneous data su…

cs.CL2026

Organizing, Orchestrating, and Benchmarking Agent Skills at Ecosystem Scale

Hao Li, Chunjiang Mu, Jianhao Chen +5

The rapid proliferation of Claude agent skills has raised the central question of how to effectively leverage, manage, and scale the agent skill ecosystem. In this paper, we propos…

cs.CL2025

Beyond GPT-5: Making LLMs Cheaper and Better via Performance-Efficiency Optimized Routing

Yiqun Zhang, Hao Li, Jianhao Chen +4

Balancing performance and efficiency is a central challenge in large language model (LLM) advancement. GPT-5 addresses this with test-time routing, dynamically assigning queries to…