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20242026
most citedWhat to Retrieve for Effective Retrieval-Augmented Code Generation? An Empirical Study and Beyond

1 citations · 2 across the 16 of their papers we have counts for

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cs.CL2026

Experience Funnel: A State-Policy Alternating Loop for Self-Evolving Agents

Wenbo Gao, Zhaomou Song, Zhiyuan Ji +7

Autonomous agents powered by large language models (LLMs) continuously accumulate experience through interaction, creating an opportunity to improve future behavior through self-ev…

cs.LG2026

How Does mHC Use Its Residual Streams? Selective Routing and Near-Identity Mixing

Pengxiang Zhao, Xing Li, Xianzhi Yu +2

Hyper-Connections and their manifold-constrained variant mHC widen a residual pathway from one stream to n, yet how trained models use this capacity remains unclear: how broadly bl…

cs.CL2026

Unleashing Low-Bit Inference on Ascend NPUs: A Comprehensive Evaluation of HiFloat Formats

Pengxiang Zhao, Hui-Ling Zhen, Xing Li +10

As LLMs scale, low-bit floating-point formats like MXFP and NVFP4 offer new opportunities for precision and efficiency. In this work, we evaluate HiFloat (HiF8 and HiF4), a family…

cs.CL2026

What Matters For Safety Alignment?

Xing Li, Hui-Ling Zhen, Lihao Yin +3

This paper presents a comprehensive empirical study on the safety alignment capabilities. We evaluate what matters for safety alignment in LLMs and LRMs to provide essential insigh…

cs.AI2026

ReThinker: Scientific Reasoning by Rethinking with Guided Reflection and Confidence Control

Zhentao Tang, Yuqi Cui, Shixiong Kai +10

Expert-level scientific reasoning remains challenging for large language models, particularly on benchmarks such as Humanity's Last Exam (HLE), where rigid tool pipelines, brittle…

cs.CL2026

Beyond Speedup -- Utilizing KV Cache for Sampling and Reasoning

Zeyu Xing, Xing Li, Hui-Ling Zhen +2

KV caches, typically used only to speed up autoregressive decoding, encode contextual information that can be reused for downstream tasks at no extra cost. We propose treating the…